Search results for: multi-temporal image classification
2638 Direct Integration of 3D Ultrasound Scans with Patient Educational Mobile Application
Authors: Zafar Iqbal, Eugene Chan, Fareed Ahmed, Mohamed Jama, Avez Rizvi
Abstract:
Advancements in Ultrasound Technology have enabled machines to capture 3D and 4D images with intricate features of the growing fetus. Sonographers can now capture clear 3D images and 4D videos of the fetus, especially of the face. Fetal faces are often seen on the ultrasound scan of the third trimester where anatomical features become more defined. Parents often want 3D/4D images and videos of their ultrasounds, and particularly image that capture the child’s face. Sidra Medicine developed a patient education mobile app called 10 Moons to improve care and provide useful information during the length of their pregnancy. In addition to general information, we built the ability to send ultrasound images directly from the modality to the mobile application, allowing expectant mothers to easily store and share images of their baby. 10 Moons represent the length of the pregnancy on a lunar calendar, which has both cultural and religious significance in the Middle East. During the third trimester scan, sonographers can capture 3D pictures of the fetus. Ultrasound machines are connected with a local 10 Moons Server with a Digital Imaging and Communications in Medicine (DICOM) application running on it. Sonographers are able to send images directly to the DICOM server by a preprogrammed button on the ultrasound modality. Mothers can also request which pictures they would like to be available on the app. An internally built DICOM application receives the image and saves the patient information from DICOM header (for verification purpose). The application also anonymizes the image by removing all the DICOM header information and subsequently converts it into a lossless JPEG. Finally, and the application passes the image to the mobile application server. On the 10 Moons mobile app – patients enter their Medical Record Number (MRN) and Date of Birth (DOB) to receive a One Time Password (OTP) for security reasons to view the images. Patients can also share the images anonymized images with friends and family. Furthermore, patients can also request 3D printed mementos of their child through 10 Moons. 10 Moons is unique patient education and information application where expected mothers can also see 3D ultrasound images of their children. Sidra Medicine staff has the added benefit of a full content management administrative backend where updates to content can be made. The app is available on secure infrastructure with both local and public interfaces. The application is also available in both English and Arabic languages to facilitate most of the patients in the region. Innovation is at the heart of modern healthcare management. With Innovation being one of Sidra Medicine’s core values, our 10 Moons application provides expectant mothers with unique educational content as well as the ability to store and share images of their child and purchase 3D printed mementos.Keywords: patient educational mobile application, ultrasound images, digital imaging and communications in medicine (DICOM), imaging informatics
Procedia PDF Downloads 1402637 Design of Liquid Crystal Based Interface to Study the Interaction of Gram Negative Bacterial Endotoxin with Milk Protein Lactoferrin
Authors: Dibyendu Das, Santanu Kumar Pal
Abstract:
Milk protein lactoferrin (Lf) exhibits potent antibacterial activity due to its interaction with Gram-negative bacterial cell membrane component, lipopolysaccharide (LPS). This paper represents fabrication of new Liquid crystals (LCs) based biosensors to explore the interaction between Lf and LPS. LPS self-assembled at aqueous/LCs interface and orients interfacial nematic 4-cyano-4’- pentylbiphenyl (5CB) LCs in a homeotropic fashion (exhibiting dark optical image under polarized optical microscope). Interestingly, on the exposure of Lf on LPS decorated aqueous/LCs interface, an optical image of LCs changed from dark to bright indicating an ordering alteration of interfacial LCs from homeotropic to tilted/planar state. The ordering transition reflects strong binding between Lf and interfacial LPS that, in turn, perturbs the orientation of LCs. With the help of epifluorescence microscopy, we further affirmed the interfacial LPS-Lf binding event by imaging the presence of FITC tagged Lf at the LPS laden aqueous/LCs interface. Finally, we have investigated the conformational behavior of Lf in solution as well as in the presence of LPS using Circular Dichroism (CD) spectroscopy and further reconfirmed with Vibrational Circular Dichroism (VCD) spectroscopy where we found that Lf undergoes alpha-helix to random coil-like structure in the presence of LPS. As a whole the entire results described in this paper establish a robust approach to envisage the interaction between LPS and Lf through the ordering transitions of LCs at aqueous/LCs interface.Keywords: endotoxin, interface, lactoferrin, lipopolysaccharide
Procedia PDF Downloads 2662636 Influence of Geologic and Geotechnical Dataset Resolution on Regional Liquefaction Assessment of the Lower Wairau Plains
Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense
Abstract:
The Wairau Plains are located in the northeast of the South Island of New Zealand, with alluvial deposits of fine-grained silts and sands combined with low-lying topography suggesting the presence of liquefiable deposits over significant portions of the region. Liquefaction manifestations were observed in past earthquakes, including the 1848 Marlborough and 1855 Wairarapa earthquakes, and more recently during the 2013 Lake Grassmere and 2016 Kaikōura earthquakes. Therefore, a good understanding of the deposits that may be susceptible to liquefaction is important for land use planning in the region and to allow developers and asset owners to appropriately address their risk. For this purpose, multiple approaches have been employed to develop regional-scale maps showing the liquefaction vulnerability categories for the region. After applying semi-qualitative criteria linked to geologic age and deposit type, the higher resolution surface mapping of geomorphologic characteristics encompassing the Wairau River and the Opaoa River was used for screening. A detailed basin geologic model developed for groundwater modelling was analysed to provide a higher level of resolution than the surface-geology based classification. This is used to identify the thickness of near-surface gravel deposits, providing an improved understanding of the presence or lack of potentially non-liquefiable crust deposits. This paper describes the methodology adopted for this project and focuses on the influence of geomorphic characteristics and analysis of the detailed geologic basin model on the liquefaction classification of the Lower Wairau Plains.Keywords: liquefaction, earthquake, cone penetration test, mapping, liquefaction-induced damage
Procedia PDF Downloads 1762635 Pruning Algorithm for the Minimum Rule Reduct Generation
Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan
Abstract:
In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.Keywords: rough sets, decision rules, rule induction, classification
Procedia PDF Downloads 5282634 Cosmetic Surgery on the Rise: The Impact of Remote Communication
Authors: Bruno Di Pace, Roxanne H. Padley
Abstract:
Aims: The recent increase in remote video interaction has increased the number of requests for teleconsultations with plastic surgeons in private practice (70% in the UK and 64% in the USA). This study investigated the motivations for such an increase and the underlying psychological impact on patients. Method: An anonymous web-based poll of 8 questions was designed and distributed to patients seeking cosmetic surgery through social networks in both Italy and the UK. The questions gathered responses regarding 1. Reasons for pursuing cosmetic surgery; 2. The effects of delays caused by the SARS-COV-2 pandemic; 3. The effects on mood; 4. The influence of video conferencing on body-image perception. Results: 85 respondents completed the online poll. Overall, 68% of respondents stated that seeing themselves more frequently online had influenced their decision to seek cosmetic surgery. The types of surgeries indicated were predominantly to the upper body and face (82%). Delays and access to surgeons during the pandemic were perceived as negatively impacting patients' moods (95%). Body-image perception and self-esteem were lower than in the pre-pandemic, particularly during lockdown (72%). Patients were more inclined to undergo cosmetic surgery during the pandemic, both due to the wish to improve their “lockdown face” for video conferencing (77%) and also due to the benefits of home recovery while in smart working (58%). Conclusions: Overall, findings suggest that video conferencing has led to a significant increase in requests for cosmetic surgery and the so-called “Zoom Boom” effect.Keywords: cosmetic surgery, remote communication, telehealth, zoom boom
Procedia PDF Downloads 1792633 Intergenerational Class Mobility in Greece: A Cross-Cohort Analysis with Evidence from European Union-Statistics on Income and Living Conditions
Authors: G. Stamatopoulou, M. Symeonaki, C. Michalopoulou
Abstract:
In this work, we study the intergenerational social mobility in Greece, in order to provide up-to-date evidence on the changes in the mobility patterns throughout the years. An analysis for both men and women aged between 25-64 years old is carried out. Three main research objectives are addressed. First, we aim to examine the relationship between the socio-economic status of parents and their children. Secondly, we investigate the evolution of the mobility patterns between different birth cohorts. Finally, the role of education is explored in shaping the mobility patterns. For the analysis, we draw data on both parental and individuals' social outcomes from different national databases. The social class of origins and destination is measured according to the European Socio-Economic Classification (ESeC), while the respondents' educational attainment is coded into categories based on the International Standard Classification of Education (ISCED). Applying the Markov transition probability theory, and a range of measures and models, this work focuses on the magnitude and the direction of the movements that take place in the Greek labour market, as well as the level of social fluidity. Three-way mobility tables are presented, where the transition probabilities between the classes of destination and origins are calculated for different cohorts. Additionally, a range of absolute and relative mobility rates, as well as distance measures, are presented. The study covers a large time span beginning in 1940 until 1995, shedding light on the effects of the national institutional processes on the social movements of individuals. Given the evidence on the mobility patterns of the most recent birth cohorts, we also investigate the possible effects of the 2008 economic crisis.Keywords: cohort analysis, education, Greece, intergenerational mobility, social class
Procedia PDF Downloads 1292632 Reconfigurable Device for 3D Visualization of Three Dimensional Surfaces
Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha
Abstract:
The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.Keywords: visualization, 3D models, servo motors, C# programming language
Procedia PDF Downloads 3422631 A Bayesian Classification System for Facilitating an Institutional Risk Profile Definition
Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan
Abstract:
This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.Keywords: linked open data, information integration, digital libraries, data mining
Procedia PDF Downloads 4262630 Food Insecurity Assessment, Consumption Pattern and Implications of Integrated Food Security Phase Classification: Evidence from Sudan
Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed
Abstract:
This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis
Procedia PDF Downloads 742629 An Analysis on Clustering Based Gene Selection and Classification for Gene Expression Data
Authors: K. Sathishkumar, V. Thiagarasu
Abstract:
Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.Keywords: microarray technology, gene expression data, clustering, gene Selection
Procedia PDF Downloads 3232628 Power Quality Modeling Using Recognition Learning Methods for Waveform Disturbances
Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim
Abstract:
This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering
Procedia PDF Downloads 1862627 Integrated Geophysical Approach for Subsurface Delineation in Srinagar, Uttarakhand, India
Authors: Pradeep Kumar Singh Chauhan, Gayatri Devi, Zamir Ahmad, Komal Chauhan, Abha Mittal
Abstract:
The application of geophysical methods to study the subsurface profile for site investigation is becoming popular globally. These methods are non-destructive and provide the image of subsurface at shallow depths. Seismic refraction method is one of the most common and efficient method being used for civil engineering site investigations particularly for knowing the seismic velocity of the subsurface layers. Resistivity imaging technique is a geo-electrical method used to image the subsurface, water bearing zone, bedrock and layer thickness. Integrated approach combining seismic refraction and 2-D resistivity imaging will provide a better and reliable picture of the subsurface. These are economical and less time-consuming field survey which provide high resolution image of the subsurface. Geophysical surveys carried out in this study include seismic refraction and 2D resistivity imaging method for delineation of sub-surface strata in different parts of Srinagar, Garhwal Himalaya, India. The aim of this survey was to map the shallow subsurface in terms of geological and geophysical properties mainly P-wave velocity, resistivity, layer thickness, and lithology of the area. Both sides of the river, Alaknanda which flows through the centre of the city, have been covered by taking two profiles on each side using both methods. Seismic and electrical surveys were carried out at the same locations to complement the results of each other. The seismic refraction survey was carried out using ABEM TeraLoc 24 channel Seismograph and 2D resistivity imaging was performed using ABEM Terrameter LS equipment. The results show three distinct layers on both sides of the river up to the depth of 20 m. The subsurface is divided into three distinct layers namely, alluvium extending up to, 3 m depth, conglomerate zone lying between the depth of 3 m to 15 m, and compacted pebbles and cobbles beyond 15 m. P-wave velocity in top layer is found in the range of 400 – 600 m/s, in second layer it varies from 700 – 1100 m/s and in the third layer it is 1500 – 3300 m/s. The resistivity results also show similar pattern and were in good agreement with seismic refraction results. The results obtained in this study were validated with an available exposed river scar at one site. The study established the efficacy of geophysical methods for subsurface investigations.Keywords: 2D resistivity imaging, P-wave velocity, seismic refraction survey, subsurface
Procedia PDF Downloads 2582626 Multi-Temporal Cloud Detection and Removal in Satellite Imagery for Land Resources Investigation
Authors: Feng Yin
Abstract:
Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation
Procedia PDF Downloads 2782625 Harnessing Emerging Creative Technology for Knowledge Discovery of Multiwavelenght Datasets
Authors: Basiru Amuneni
Abstract:
Astronomy is one domain with a rise in data. Traditional tools for data management have been employed in the quest for knowledge discovery. However, these traditional tools become limited in the face of big. One means of maximizing knowledge discovery for big data is the use of scientific visualisation. The aim of the work is to explore the possibilities offered by emerging creative technologies of Virtual Reality (VR) systems and game engines to visualize multiwavelength datasets. Game Engines are primarily used for developing video games, however their advanced graphics could be exploited for scientific visualization which provides a means to graphically illustrate scientific data to ease human comprehension. Modern astronomy is now in the era of multiwavelength data where a single galaxy for example, is captured by the telescope several times and at different electromagnetic wavelength to have a more comprehensive picture of the physical characteristics of the galaxy. Visualising this in an immersive environment would be more intuitive and natural for an observer. This work presents a standalone VR application that accesses galaxy FITS files. The application was built using the Unity Game Engine for the graphics underpinning and the OpenXR API for the VR infrastructure. The work used a methodology known as Design Science Research (DSR) which entails the act of ‘using design as a research method or technique’. The key stages of the galaxy modelling pipeline are FITS data preparation, Galaxy Modelling, Unity 3D Visualisation and VR Display. The FITS data format cannot be read by the Unity Game Engine directly. A DLL (CSHARPFITS) which provides a native support for reading and writing FITS files was used. The Galaxy modeller uses an approach that integrates cleaned FITS image pixels into the graphics pipeline of the Unity3d game Engine. The cleaned FITS images are then input to the galaxy modeller pipeline phase, which has a pre-processing script that extracts, pixel, galaxy world position, and colour maps the FITS image pixels. The user can visualise image galaxies in different light bands, control the blend of the image with similar images from different sources or fuse images for a holistic view. The framework will allow users to build tools to realise complex workflows for public outreach and possibly scientific work with increased scalability, near real time interactivity with ease of access. The application is presented in an immersive environment and can use all commercially available headset built on the OpenXR API. The user can select galaxies in the scene, teleport to the galaxy, pan, zoom in/out, and change colour gradients of the galaxy. The findings and design lessons learnt in the implementation of different use cases will contribute to the development and design of game-based visualisation tools in immersive environment by enabling informed decisions to be made.Keywords: astronomy, visualisation, multiwavelenght dataset, virtual reality
Procedia PDF Downloads 912624 Detecting Indigenous Languages: A System for Maya Text Profiling and Machine Learning Classification Techniques
Authors: Alejandro Molina-Villegas, Silvia Fernández-Sabido, Eduardo Mendoza-Vargas, Fátima Miranda-Pestaña
Abstract:
The automatic detection of indigenous languages in digital texts is essential to promote their inclusion in digital media. Underrepresented languages, such as Maya, are often excluded from language detection tools like Google’s language-detection library, LANGDETECT. This study addresses these limitations by developing a hybrid language detection solution that accurately distinguishes Maya (YUA) from Spanish (ES). Two strategies are employed: the first focuses on creating a profile for the Maya language within the LANGDETECT library, while the second involves training a Naive Bayes classification model with two categories, YUA and ES. The process includes comprehensive data preprocessing steps, such as cleaning, normalization, tokenization, and n-gram counting, applied to text samples collected from various sources, including articles from La Jornada Maya, a major newspaper in Mexico and the only media outlet that includes a Maya section. After the training phase, a portion of the data is used to create the YUA profile within LANGDETECT, which achieves an accuracy rate above 95% in identifying the Maya language during testing. Additionally, the Naive Bayes classifier, trained and tested on the same database, achieves an accuracy close to 98% in distinguishing between Maya and Spanish, with further validation through F1 score, recall, and logarithmic scoring, without signs of overfitting. This strategy, which combines the LANGDETECT profile with a Naive Bayes model, highlights an adaptable framework that can be extended to other underrepresented languages in future research. This fills a gap in Natural Language Processing and supports the preservation and revitalization of these languages.Keywords: indigenous languages, language detection, Maya language, Naive Bayes classifier, natural language processing, low-resource languages
Procedia PDF Downloads 162623 Estimating the Ladder Angle and the Camera Position From a 2D Photograph Based on Applications of Projective Geometry and Matrix Analysis
Authors: Inigo Beckett
Abstract:
In forensic investigations, it is often the case that the most potentially useful recorded evidence derives from coincidental imagery, recorded immediately before or during an incident, and that during the incident (e.g. a ‘failure’ or fire event), the evidence is changed or destroyed. To an image analysis expert involved in photogrammetric analysis for Civil or Criminal Proceedings, traditional computer vision methods involving calibrated cameras is often not appropriate because image metadata cannot be relied upon. This paper presents an approach for resolving this problem, considering in particular and by way of a case study, the angle of a simple ladder shown in a photograph. The UK Health and Safety Executive (HSE) guidance document published in 2014 (INDG455) advises that a leaning ladder should be erected at 75 degrees to the horizontal axis. Personal injury cases can arise in the construction industry because a ladder is too steep or too shallow. Ad-hoc photographs of such ladders in their incident position provide a basis for analysis of their angle. This paper presents a direct approach for ascertaining the position of the camera and the angle of the ladder simultaneously from the photograph(s) by way of a workflow that encompasses a novel application of projective geometry and matrix analysis. Mathematical analysis shows that for a given pixel ratio of directly measured collinear points (i.e. features that lie on the same line segment) from the 2D digital photograph with respect to a given viewing point, we can constrain the 3D camera position to a surface of a sphere in the scene. Depending on what we know about the ladder, we can enforce another independent constraint on the possible camera positions which enables us to constrain the possible positions even further. Experiments were conducted using synthetic and real-world data. The synthetic data modeled a vertical plane with a ladder on a horizontally flat plane resting against a vertical wall. The real-world data was captured using an Apple iPhone 13 Pro and 3D laser scan survey data whereby a ladder was placed in a known location and angle to the vertical axis. For each case, we calculated camera positions and the ladder angles using this method and cross-compared them against their respective ‘true’ values.Keywords: image analysis, projective geometry, homography, photogrammetry, ladders, Forensics, Mathematical modeling, planar geometry, matrix analysis, collinear, cameras, photographs
Procedia PDF Downloads 522622 Selection of New Business in Brazilian Companies Incubators through Hierarchical Methodology
Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira
Abstract:
In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator
Procedia PDF Downloads 3732621 Accurate Mass Segmentation Using U-Net Deep Learning Architecture for Improved Cancer Detection
Authors: Ali Hamza
Abstract:
Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network
Procedia PDF Downloads 842620 A Technique for Planning the Application of Buttress Plate in the Medial Tibial Plateau Using the Preoperative CT Scan
Authors: P. Panwalkar, K. Veravalli, R. Gwynn, M. Tofighi, R. Clement, A. Mofidi
Abstract:
When operating on tibial plateau fracture especially medial tibial plateau, it has regularly been said “where do I put my thumb to reduce the fracture”. This refers to the ideal placement of the buttress device to hold the fracture till union. The aim of this study was to see if one can identify this sweet spot using a CT scan. Methods: Forty-five tibial plateau fractures with medial plateau involvement were identified and included in the study. The preoperative CT scans were analysed and the medial plateau involvement pattern was classified based on modified radiological classification by Yukata et-al of stress fracture of medial tibial plateau. The involvement of part of plateau was compared with position of buttress plate position which was classified as medial posteromedial or both. Presence and position of the buttress was compared with ability to achieve and hold the reduction of the fracture till union. Results: Thirteen fractures were type-1 fracture, 19 fractures were type-2 fracture and 13 fractures were type-3 fracture. Sixteen fractures were buttressed correctly according to the potential deformity and twenty-six fractures were not buttressed and three fractures were partly buttressed correctly. No fracture was over butressed! When the fracture was buttressed correctly the rate of the malunion was 0%. When fracture was partly buttressed 33% were anatomically united and 66% were united in the plane of buttress. When buttress was not used, 14 were malunited, one malunited in one of the two planes of deformity and eleven anatomically healed (of which 9 were non displaced!). Buttressing resulted in statistically significant lower mal-union rate (x2=7.8, p=0.0052). Conclusion: The classification based on involvement of medial condyle can identify the placement of buttress plate in the tibial plateau. The correct placement of the buttress plate results in predictably satisfactory union. There may be a correlation between injury shape of the tibial plateau and the fracture type.Keywords: knee, tibial plateau, trauma, CT scan, surgery
Procedia PDF Downloads 1462619 Hope in the Ruins of 'Ozymandias': Reimagining Temporal Horizons in Felicia Hemans 'the Image in Lava'
Authors: Lauren Schuldt Wilson
Abstract:
Felicia Hemans’ memorializing of the unwritten lives of women and the consequent allowance for marginalized voices to remember and be remembered has been considered by many critics in terms of ekphrasis and elegy, terms which privilege the question of whether Hemans’ poeticizing can represent lost voices of history or only her poetic expression. Amy Gates, Brian Elliott, and others point out Hemans’ acknowledgement of the self-projection necessary for imaginatively filling the absences of unrecorded histories. Yet, few have examined the complex temporal positioning Hemans inscribes in these moments of self-projection and imaginative historicizing. In poems like ‘The Image in Lava,’ Hemans maps not only a lost past, but also a lost potential future onto the image of a dead infant in its mother’s arms, the discovery and consideration of which moves the imagined viewer to recover and incorporate the ‘hope’ encapsulated in the figure of the infant into a reevaluation of national time embodied by the ‘relics / Left by the pomps of old.’ By examining Hemans’ acknowledgement and response to Percy Bysshe Shelley’s ‘Ozymandias,’ this essay explores how Hemans’ depictions of imaginative historicizing open new horizons of possibility and reevaluate temporal value structures by imagining previously undiscovered or unexplored potentialities of the past. Where Shelley’s poem mocks the futility of national power and time, this essay outlines Hemans’ suggestion of alternative threads of identity and temporal meaning-making which, regardless of historical veracity, exist outside of and against the structures Shelley challenges. Counter to previous readings of Hemans’ poem as celebration of either recovered or poetically constructed maternal love, this essay argues that Hemans offers a meditation on sites of reproduction—both of personal reproductive futurity and of national reproduction of power. This meditation culminates in Hemans’ gesturing towards a method of historicism by which the imagined viewer reinvigorates the sterile, ‘shattered visage’ of national time by forming temporal identity through the imagining of trans-historical hope inscribed on the infant body of the universal, individual subject rather than the broken monument of the king.Keywords: futurity, national temporalities, reproduction, revisionary histories
Procedia PDF Downloads 1662618 Accurate Positioning Method of Indoor Plastering Robot Based on Line Laser
Authors: Guanqiao Wang, Hongyang Yu
Abstract:
There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. There- fore, robots appear more and more frequently in the construction industry. Navigation and positioning are very important tasks for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radiofrequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered, or the error of plastering the wall is large. A new positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.Keywords: indoor plastering robot, navigation, precise positioning, line laser, image processing
Procedia PDF Downloads 1482617 Rapid Flood Damage Assessment of Population and Crops Using Remotely Sensed Data
Authors: Urooj Saeed, Sajid Rashid Ahmad, Iqra Khalid, Sahar Mirza, Imtiaz Younas
Abstract:
Pakistan, a flood-prone country, has experienced worst floods in the recent past which have caused extensive damage to the urban and rural areas by loss of lives, damage to infrastructure and agricultural fields. Poor flood management system in the country has projected the risks of damages as the increasing frequency and magnitude of floods are felt as a consequence of climate change; affecting national economy directly or indirectly. To combat the needs of flood emergency, this paper focuses on remotely sensed data based approach for rapid mapping and monitoring of flood extent and its damages so that fast dissemination of information can be done, from local to national level. In this research study, spatial extent of the flooding caused by heavy rains of 2014 has been mapped by using space borne data to assess the crop damages and affected population in sixteen districts of Punjab. For this purpose, moderate resolution imaging spectroradiometer (MODIS) was used to daily mark the flood extent by using Normalised Difference Water Index (NDWI). The highest flood value data was integrated with the LandScan 2014, 1km x 1km grid based population, to calculate the affected population in flood hazard zone. It was estimated that the floods covered an area of 16,870 square kilometers, with 3.0 million population affected. Moreover, to assess the flood damages, Object Based Image Analysis (OBIA) aided with spectral signatures was applied on Landsat image to attain the thematic layers of healthy (0.54 million acre) and damaged crops (0.43 million acre). The study yields that the population of Jhang district (28% of 2.5 million population) was affected the most. Whereas, in terms of crops, Jhang and Muzzafargarh are the ‘highest damaged’ ranked district of floods 2014 in Punjab. This study was completed within 24 hours of the peak flood time, and proves to be an effective methodology for rapid assessment of damages due to flood hazardKeywords: flood hazard, space borne data, object based image analysis, rapid damage assessment
Procedia PDF Downloads 3282616 Using Hierarchical Methodology to Assist the Selection of New Business in Brazilian Companies Incubators
Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira
Abstract:
In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist in this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator
Procedia PDF Downloads 4022615 Proposed Organizational Development Interventions in Managing Occupational Stressors for Business Schools in Batangas City
Authors: Marlon P. Perez
Abstract:
The study intended to determine the level of occupational stress that was experienced by faculty members of private and public business schools in Batangas City with the end in view of proposing organizational development interventions in managing occupational stressors. Stressors such as factors intrinsic to the job, role in the organization, relationships at work, career development and organizational structure and climate were used as determinants of occupational stress level. Descriptive method of research was used as its research design. There were only 64 full-time faculty members coming from private and public business schools in Batangas City – University of Batangas, Lyceum of the Philippines University-Batangas, Golden Gate Colleges, Batangas State University and Colegio ng Lungsod ng Batangas. Survey questionnaire was used as data gathering instrument. It was found out that all occupational stressors were assessed stressful when grouped according to its classification of tertiary schools while response of subject respondents differs on their assessment of occupational stressors. Age variable has become significantly related to respondents’ assessments on factors intrinsic to the job and career development; however, it was not significantly related to role in the organization, relationships at work and organizational structure and climate. On the other hand, gender, marital status, highest educational attainment, employment status, length of service, area of specialization and classification of tertiary school were revealed to be not significantly related to all occupational stressors. Various organizational development interventions have been proposed to manage the occupational stressors that are experienced by business faculty members in the institution.Keywords: occupational stress, business school, organizational development, intervention, stressors, faculty members, assessment, manage
Procedia PDF Downloads 4312614 Reduplication in Dhiyan: An Indo-Aryan Language of Assam
Authors: S. Sulochana Singha
Abstract:
Dhiyan or Dehan is the name of the community and language spoken by the Koch-Rajbangshi people of Barak Valley of Assam. Ethnically, they are Mongoloids, and their language belongs to the Indo-Aryan language family. However, Dhiyan is absent in any classification of Indo-Aryan languages. So the classification of Dhiyan language under the Indo-Aryan language family is completely based on the shared typological features of the other Indo-Aryan languages. Typologically, Dhiyan is an agglutinating language, and it shares many features of Indo-Aryan languages like presence of aspirated voiced stops, non-tonal, verb-person agreement, adjectives as different word class, prominent tense and subject object verb word order. Reduplication is a productive word-formation process in Dhiyan. Besides it also expresses plurality, intensification, and distributive. Generally, reduplication in Dhiyan can be at the morphological or lexical level. Morphological reduplication in Dhiyan involves expressives which includes onomatopoeias, sound symbolism, idiophones, and imitatives. Lexical reduplication in the language can be formed by echo formations and word reduplication. Echo formation in Dhiyan is formed by partial repetition from the base word which can be either consonant alternation or vowel alternation. The consonant alternation is basically found in onset position while the alternation of vowel is basically found in open syllable particularly in final syllable. Word reduplication involves reduplication of nouns, interrogatives, adjectives, and numerals which further can be class changing or class maintaining reduplication. The process of reduplication can be partial or complete whether it is lexical or morphological. The present paper is an attempt to describe some aspects of the formation, function, and usage of reduplications in Dhiyan which is mainly spoken in ten villages in the Eastern part of Barak River in the Cachar District of Assam.Keywords: Barak-Valley, Dhiyan, Indo-Aryan, reduplication
Procedia PDF Downloads 2172613 Rapid Fetal MRI Using SSFSE, FIESTA and FSPGR Techniques
Authors: Chen-Chang Lee, Po-Chou Chen, Jo-Chi Jao, Chun-Chung Lui, Leung-Chit Tsang, Lain-Chyr Hwang
Abstract:
Fetal Magnetic Resonance Imaging (MRI) is a challenge task because the fetal movements could cause motion artifact in MR images. The remedy to overcome this problem is to use fast scanning pulse sequences. The Single-Shot Fast Spin-Echo (SSFSE) T2-weighted imaging technique is routinely performed and often used as a gold standard in clinical examinations. Fast spoiled gradient-echo (FSPGR) T1-Weighted Imaging (T1WI) is often used to identify fat, calcification and hemorrhage. Fast Imaging Employing Steady-State Acquisition (FIESTA) is commonly used to identify fetal structures as well as the heart and vessels. The contrast of FIESTA image is related to T1/T2 and is different from that of SSFSE. The advantages and disadvantages of these two scanning sequences for fetal imaging have not been clearly demonstrated yet. This study aimed to compare these three rapid MRI techniques (SSFSE, FIESTA, and FSPGR) for fetal MRI examinations. The image qualities and influencing factors among these three techniques were explored. A 1.5T GE Discovery 450 clinical MR scanner with an eight-channel high-resolution abdominal coil was used in this study. Twenty-five pregnant women were recruited to enroll fetal MRI examination with SSFSE, FIESTA and FSPGR scanning. Multi-oriented and multi-slice images were acquired. Afterwards, MR images were interpreted and scored by two senior radiologists. The results showed that both SSFSE and T2W-FIESTA can provide good image quality among these three rapid imaging techniques. Vessel signals on FIESTA images are higher than those on SSFSE images. The Specific Absorption Rate (SAR) of FIESTA is lower than that of the others two techniques, but it is prone to cause banding artifacts. FSPGR-T1WI renders lower Signal-to-Noise Ratio (SNR) because it severely suffers from the impact of maternal and fetal movements. The scan times for these three scanning sequences were 25 sec (T2W-SSFSE), 20 sec (FIESTA) and 18 sec (FSPGR). In conclusion, all these three rapid MR scanning sequences can produce high contrast and high spatial resolution images. The scan time can be shortened by incorporating parallel imaging techniques so that the motion artifacts caused by fetal movements can be reduced. Having good understanding of the characteristics of these three rapid MRI techniques is helpful for technologists to obtain reproducible fetal anatomy images with high quality for prenatal diagnosis.Keywords: fetal MRI, FIESTA, FSPGR, motion artifact, SSFSE
Procedia PDF Downloads 5302612 Video Compression Using Contourlet Transform
Authors: Delara Kazempour, Mashallah Abasi Dezfuli, Reza Javidan
Abstract:
Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform.Keywords: video compression, contourlet transform, discrete cosine transform, wavelet transform
Procedia PDF Downloads 4442611 An Investigation into Computer Vision Methods to Identify Material Other Than Grapes in Harvested Wine Grape Loads
Authors: Riaan Kleyn
Abstract:
Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.Keywords: computer vision, wine grapes, machine learning, machine harvested grapes
Procedia PDF Downloads 942610 Hybridization of Manually Extracted and Convolutional Features for Classification of Chest X-Ray of COVID-19
Authors: M. Bilal Ishfaq, Adnan N. Qureshi
Abstract:
COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.Keywords: COVID-19, feature engineering, artificial neural networks, radiology images
Procedia PDF Downloads 752609 Preprocessing and Fusion of Multiple Representation of Finger Vein patterns using Conventional and Machine Learning techniques
Authors: Tomas Trainys, Algimantas Venckauskas
Abstract:
Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.
Procedia PDF Downloads 150