Search results for: quantum image encryption
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3457

Search results for: quantum image encryption

2707 Level Set Based Extraction and Update of Lake Contours Using Multi-Temporal Satellite Images

Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

Abstract:

The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

Procedia PDF Downloads 364
2706 Detecting the Blood of Femoral and Carotid Artery of Swine Using Photoacoustic Tomography in-vivo

Authors: M. Y. Lee, S. H. Park, S. M. Yu, H. S. Jo, C. G. Song

Abstract:

Photoacoustic imaging is the imaging technology that combines the optical imaging with ultrasound. It also provides the high contrast and resolution due to optical and ultrasound imaging, respectively. For these reasons, many studies take experiment in order to apply this method for many diagnoses. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer. In this study, we conduct the experiment using swine and detect the blood of carotid artery and femoral artery. We measured the blood of femoral and carotid artery of swine and reconstructed the image using 950nm due to the HbO₂ absorption coefficient. The photoacoustic image is overlaid with ultrasound image in order to match the position. In blood of artery, major composition of blood is HbO₂. In this result, we can measure the blood of artery.

Keywords: photoacoustic tomography, swine artery, carotid artery, femoral artery

Procedia PDF Downloads 248
2705 Challenges for Tourism Development in Algeria: Perspectives of Algerian Tourism Suppliers

Authors: Nour-Elhouda Lecheheb

Abstract:

Despite substantial tourism potentials, the Algerian tourism industry has faced a number of challenges, including the government heavy dependence on the energy sector, negative perception in the West, and a lack of effective resource management and marketing. This paper attempts to discuss the challenges hindering the development of the Algerian tourism industry from the perspective of the official tourism suppliers in Algeria both in the public and private sectors. A total of 10 semi-structured interviews were conducted during a field-trip to Algiers, Algeria, in September 2019. From the analysis of the interviews, it is evident that the Algerian tourism suppliers face a number of challenges mainly the country’s negative image in the West and a significant lack of political and financial support to contest this negative image effectively and sufficiently.

Keywords: Algerian tourism, destination development, destination image, tourism suppliers

Procedia PDF Downloads 257
2704 Leukocyte Detection Using Image Stitching and Color Overlapping Windows

Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

Abstract:

Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

Procedia PDF Downloads 308
2703 Development of a Few-View Computed Tomographic Reconstruction Algorithm Using Multi-Directional Total Variation

Authors: Chia Jui Hsieh, Jyh Cheng Chen, Chih Wei Kuo, Ruei Teng Wang, Woei Chyn Chu

Abstract:

Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better.

Keywords: compressed sensing (CS), low-dose CT reconstruction, total variation (TV), multi-directional gradient operator

Procedia PDF Downloads 255
2702 Fathers and Daughters: Their Relationship and Its Impact on Body Image and Mental Health

Authors: John Toussaint

Abstract:

Objective: Our society is suffering from an epidemic of body image dissatisfaction, and related disorders appear to be increasing globally for children. There is much to indicate that children's body image and eating attitudes are being affected negatively by socio-cultural factors such as parents, peers and media. Most studies and theories, however, have focused extensively on the daughter-mother relationship. Very few studies have investigated the role of attachment to the father as an important factor in the development of girls’ and women’s attitudes towards themselves and their bodies. Recently, data have shown that the father’s parenting style, as well as the quality of the relationship with him is crucial for the understanding of the development and persistence of body image disorders. This presentation is based on samples of participants with self-defined body image dissatisfaction, and the self-reported measures of their fathers’ parental behaviours, emotional warmth, support, or protection. Attachment theory does offer support in exploring these relationships and it is used in this presentation to assist in understanding the relationship between the father and his daughter in relation to body image and mental health. Clinical implications are also offered in respect to work with body image, eating disorders and relational therapy. Methods: As awareness of the increasing frequency of body image concerns in children grows, so too does the need for a simple, valid and reliable measure of body image. The Children's Body Image Scale (CBIS) designed in Australia, depicts seven male and females figures from which children are to choose their perceived body type and ideal body type. This was compared with a range of international body mass index (BMI) reference standards. These measures together with individual one-on-one interviews were completed by 158 children aged 7-12 years. Results: A high frequency of body image dissatisfaction was indicated in the children's responses. 55% of girls and 41% of boys said they would like to be thinner, and wished for an ideal BMI figure below the 10th percentile. This is an unhealthy and unattainable level of body fatness for the majority of children when considered in relation to the reported secular trend of their increasing average body size. Thin children were generally ranked as best and perceived as kind, happy, academically skilled, and socially successful. Fat children were perceived as unintelligent, lazy, greedy, unpopular, and unable to play physical games. Conclusions: Body image ideals and fat stereotypes are well entrenched among children. There is much to indicate that children's body image and eating attitudes are being affected negatively by sociocultural factors such as parents, peers and media. Teachers and health professionals could promote intervention programs for children involving knowledge and acceptance of genetic influences on body type; the dangerous effects of weight loss dieting; the importance of physical activity and eating healthy; and scepticism and critical analysis of mass media messages.

Keywords: body image, father attachment, mental health, eating disorders

Procedia PDF Downloads 260
2701 Media Representation of China: A Content Analysis of Coverage of China-Related Energy in the New York Times

Authors: Lian Liu

Abstract:

By analyzing the content of the New York Times' China-related energy reports, this study aims to explore the construction of China's national image by the mainstream media in the United States. The study analyzes three aspects of the coverage: topics, reporting tendencies, and countries involved. The results of the study show that economic issues are the main focus of the New York Times’ China-related energy coverage, followed by political issues and environmental issues. Overall, the coverage tendency was mainly negative, but positive coverage was dominated by science and technology issues. In addition, the study found that U.S.-China relations and Sino-Russian relations were important contexts for the construction of China's national image in the NYT's China-related energy coverage. These stories highlight China's interstate interactions with the United States, Japan, and Russia, which serve as important links in the coverage. The findings of this study reveal some characteristics and trends of the U.S. mainstream media's country image of China, which are important for a deeper understanding of the U.S.-China relationship and the media's influence on the construction of the country's image.

Keywords: media coverage, China, content analysis, visualization technology

Procedia PDF Downloads 83
2700 Bound State Problems and Functional Differential Geometry

Authors: S. Srednyak

Abstract:

We study a class of functional partial differential equations(FPDEs). This class is suggested by Quantum Field Theory. We derive general properties of solutions to such equations. In particular, we demonstrate that they lead to systems of coupled integral equations with singular kernels. We show that solutions to such hierarchies can be sought among functions with regular singularities at a countable set of subvarieties of the physical space. We also develop a formal analogy of basic constructions of differential geometry on functional manifolds, as this is necessary for in depth study of FPDEs. We also consider the case of linear overdetermined systems of functional differential equations and show that it can be completely solved in terms of formal solutions of a functional equation that is a functional analogy of a system of determined algebraic equations. This development leads us to formally define the functional analogy of algebraic geometry, which we call functional algebraic geometry. We study basic properties of functional algebraic varieties. In particular, we investigate the case of a formally discrete set of solutions. We also define and study functional analogy of discriminants. In the case of fully determined systems such that the defining functionals have regular singularities, we demonstrate that formal solutions can be sought in the class of functions with regular singularities. This case provides a practical way to apply our results to physics problems.

Keywords: functional equations, quantum field theory, holomorphic functions, Yang Mills mass gap problem, quantum chaos

Procedia PDF Downloads 70
2699 “The Day I Became a Woman” by Marziyeh Meshkiny: An Analysis of the Cinematographic Image of the Middle East

Authors: Ana Carolina Domingues

Abstract:

This work presents the preliminary results of the above-titled doctoral research. Based on this film and on Middle East authors who discuss films made by women, it has been concluded so far, that it is part of a larger movement, which together with other productions, show the perceptions of the world of these women, who see the world otherwise, for not holding positions of power. These modes of perception revealed from the encounter of women with the cameras, educate viewers to denaturalize the impressions constructed in relation to the Middle East.

Keywords: cinema, image, middle east, women

Procedia PDF Downloads 116
2698 Optimized and Secured Digital Watermarking Using Entropy, Chaotic Grid Map and Its Performance Analysis

Authors: R. Rama Kishore, Sunesh

Abstract:

This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: digital watermarking, discreate cosine transform, chaotic grid map, entropy

Procedia PDF Downloads 252
2697 Corporate Social Responsibility Initiatives in COVID-19: The Effect of CSR Motives Attributions on Advocacy

Authors: Tengku Ezni Balqiah, Fanny Martdianty, Rifelly Dewi Astuti, Mutia Nurazizah Rachmawati

Abstract:

The Corona Disease 2019 (COVID-19) pandemic has changed the world considerably and has disrupted businesses and people’s lives globally. In response to the pandemic, businesses have seen increased demand for corporate social responsibility (CSR). Businesses can increase their investments in CSR initiatives during the pandemic through various actions. This study examines how the various motives of philanthropy CSR influence perceived quality of life, company image, and advocacy. This study employed surveys of 719 respondents from seven provinces in Indonesia that had the highest number of COVID-19 cases in the country. A structural equation model was used to test the hypothesis. The results showed that value and strategic motives positively influenced the perceived quality of life and corporate image, while the egoistic motive was negatively associated with both the perceived quality of life and the image of the company. The study also suggested that advocacy was strongly related to the perceived quality of life instead of a corporate image. The results indicate that, during a pandemic, both public- (i.e. value) and firm-serving (i.e. strategic) motives can have the same impact as long as people perceive that the businesses are sincere.

Keywords: advocacy, COVID 19, CSR motive, Indonesia, quality of life

Procedia PDF Downloads 133
2696 Assessing the Applicability of Kevin Lynch’s Framework of ‘the Image of the City’ in the Case of a Walled City of Jaipur

Authors: Jay Patel

Abstract:

This Research is about investigating the ‘image’ of the city, and asks whether this ‘image’ holds any significance that can be changed. Kevin Lynch in the book ‘The image of the city’ develops a framework that breaks down the city’s image into five physical elements. These elements (Paths, Edge, Nodes, Districts, and Landmarks), according to Lynch assess the legibility of the urbanscapes, that emerged from his perception-based study in 3 different cities (New Jersey, Los Angeles, and Boston) in the USA. The aim of this research is to investigate whether Lynch’s framework can be applied within an Indian context or not. If so, what are the possibilities and whether the imageability of Indian cities can be depicted through the Lynch’s physical elements or it demands an extension to the framework by either adding or subtracting a physical attribute. For this research project, the walled city of Jaipur was selected, as it is considered one of the futuristic designed cities of all time in India. The other significant reason for choosing Jaipur was that it is a historically planned city with solid historical, touristic and local importance; allowing an opportunity to understand the application of Lynch's elements to the city's image. In other words, it provides an opportunity to examine how the disadvantages of a city's implicit programme (its relics of bygone eras) can be converted into assets by improving the imageability of the city. To obtain data, a structured semi-open ended interview method was chosen. The reason for selecting this method explicitly was to gain qualitative data from the users rather than collecting quantitative data from closed-ended questions. This allowed in-depth understanding and applicability of Kevin Lynch’s framework while assessing what needs to be added. The interviews were conducted in Jaipur that yielded varied inferences that were different from the expected learning outcomes, highlighting the need for extension on Lynch’s physical elements to achieve city’s image. Whilst analyzing the data, there were few attributes found that defined the image of Jaipur. These were categorized into two: a Physical aspect (streets and arcade entities, natural features, temples and temporary/ informal activities) and Associational aspects (History, Culture and Tradition, Medium of help in wayfinding, and intangible aspects).

Keywords: imageability, Kevin Lynch, people’s perception, assessment, associational aspects, physical aspects

Procedia PDF Downloads 196
2695 Estimation of PM10 Concentration Using Ground Measurements and Landsat 8 OLI Satellite Image

Authors: Salah Abdul Hameed Saleh, Ghada Hasan

Abstract:

The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

Procedia PDF Downloads 441
2694 Brand Extension and Customer WOM: Evidence from the Sports Industry

Authors: Jim Shih-Chiao Chin, Yu Ting Yeh, Shui Lien Chen, Yi-Fen Tsai

Abstract:

his study is taking Adidas Company as the object, explored the brand awareness directly or indirectly affects brand affect and word of mouth. First, explored the brand awareness on category fit and image fit, and examined the influence of category fit and image fit on extension attitude. This study then designates the effect of extension attitude on brand affect and word-of-mouth. The relationship of brand awareness on brand affect and word-of-mouth was also explored. The study participants are people who have purchased Adidas extension products. A total of 700 valid questionnaires were collected and statistical software AMOS 20.0 was used to examine the research hypotheses by using structural equation modeling (SEM). Finally, theoretical implications and research directions are provided for future studies.

Keywords: brand extension, brand awareness, product category fit, brand image fit, brand affect, word-of-mouth (WOM)

Procedia PDF Downloads 331
2693 Immature Palm Tree Detection Using Morphological Filter for Palm Counting with High Resolution Satellite Image

Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

Abstract:

Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

Procedia PDF Downloads 74
2692 Marker-Controlled Level-Set for Segmenting Breast Tumor from Thermal Images

Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

Abstract:

Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

Procedia PDF Downloads 378
2691 Intrusion Detection Techniques in NaaS in the Cloud: A Review

Authors: Rashid Mahmood

Abstract:

The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

Procedia PDF Downloads 318
2690 Mapping Tunnelling Parameters for Global Optimization in Big Data via Dye Laser Simulation

Authors: Sahil Imtiyaz

Abstract:

One of the biggest challenges has emerged from the ever-expanding, dynamic, and instantaneously changing space-Big Data; and to find a data point and inherit wisdom to this space is a hard task. In this paper, we reduce the space of big data in Hamiltonian formalism that is in concordance with Ising Model. For this formulation, we simulate the system using dye laser in FORTRAN and analyse the dynamics of the data point in energy well of rhodium atom. After mapping the photon intensity and pulse width with energy and potential we concluded that as we increase the energy there is also increase in probability of tunnelling up to some point and then it starts decreasing and then shows a randomizing behaviour. It is due to decoherence with the environment and hence there is a loss of ‘quantumness’. This interprets the efficiency parameter and the extent of quantum evolution. The results are strongly encouraging in favour of the use of ‘Topological Property’ as a source of information instead of the qubit.

Keywords: big data, optimization, quantum evolution, hamiltonian, dye laser, fermionic computations

Procedia PDF Downloads 192
2689 Estimation of Asphalt Pavement Surfaces Using Image Analysis Technique

Authors: Mohammad A. Khasawneh

Abstract:

Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure. The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab. Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.

Keywords: friction, image analysis, polishing, statistical analysis, texture

Procedia PDF Downloads 304
2688 Investigation of Interlayer Shear Effects in Asphalt Overlay on Existing Rigid Airfield Pavement Using Digital Image Correlation

Authors: Yuechao Lei, Lei Zhang

Abstract:

The interface shear between asphalt overlay and existing rigid airport pavements occurs due to differences in the mechanical properties of materials subjected to aircraft loading. Interlayer contact influences the mechanical characteristics of the asphalt overlay directly. However, the effective interlayer relative displacement obtained accurately using existing displacement sensors of the loading apparatus remains challenging. This study aims to utilize digital image correlation technology to enhance the accuracy of interfacial contact parameters by obtaining effective interlayer relative displacements. Composite structure specimens were prepared, and fixtures for interlayer shear tests were designed and fabricated. Subsequently, a digital image recognition scheme for required markers was designed and optimized. Effective interlayer relative displacement values were obtained through image recognition and calculation of surface markers on specimens. Finite element simulations validated the mechanical response of composite specimens with interlayer shearing. Results indicated that an optimized marking approach using the wall mending agent for surface application and color coding enhanced the image recognition quality of marking points on the specimen surface. Further image extraction provided effective interlayer relative displacement values during interlayer shear, thereby improving the accuracy of interface contact parameters. For composite structure specimens utilizing Styrene-Butadiene-Styrene (SBS) modified asphalt as the tack coat, the corresponding maximum interlayer shear stress strength was 0.6 MPa, and fracture energy was 2917 J/m2. This research provides valuable insights for investigating the impact of interlayer contact in composite pavement structures on the mechanical characteristics of asphalt overlay.

Keywords: interlayer contact, effective relative displacement, digital image correlation technology, composite pavement structure, asphalt overlay

Procedia PDF Downloads 46
2687 Deep Neural Networks for Restoration of Sky Images Affected by Static and Anisotropic Aberrations

Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

Abstract:

Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

Procedia PDF Downloads 134
2686 A Custom Convolutional Neural Network with Hue, Saturation, Value Color for Malaria Classification

Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

Abstract:

Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

Procedia PDF Downloads 86
2685 Effective Stacking of Deep Neural Models for Automated Object Recognition in Retail Stores

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 154
2684 FLIME - Fast Low Light Image Enhancement for Real-Time Video

Authors: Vinay P., Srinivas K. S.

Abstract:

Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 201
2683 Post-Quantum Resistant Edge Authentication in Large Scale Industrial Internet of Things Environments Using Aggregated Local Knowledge and Consistent Triangulation

Authors: C. P. Autry, A. W. Roscoe, Mykhailo Magal

Abstract:

We discuss the theoretical model underlying 2BPA (two-band peer authentication), a practical alternative to conventional authentication of entities and data in IoT. In essence, this involves assembling a virtual map of authentication assets in the network, typically leading to many paths of confirmation between any pair of entities. This map is continuously updated, confirmed, and evaluated. The value of authentication along multiple disjoint paths becomes very clear, and we require analogues of triangulation to extend authentication along extended paths and deliver it along all possible paths. We discover that if an attacker wants to make an honest node falsely believe she has authenticated another, then the length of the authentication paths is of little importance. This is because optimal attack strategies correspond to minimal cuts in the authentication graph and do not contain multiple edges on the same path. The authentication provided by disjoint paths normally is additive (in entropy).

Keywords: authentication, edge computing, industrial IoT, post-quantum resistance

Procedia PDF Downloads 195
2682 Parallel Random Number Generation for the Modern Supercomputer Architectures

Authors: Roman Snytsar

Abstract:

Pseudo-random numbers are often used in scientific computing such as the Monte Carlo Simulations or the Quantum Inspired Optimization. Requirements for a parallel random number generator running in the modern multi-core vector environment are more stringent than those for sequential random number generators. As well as passing the usual quality tests, the output of the parallel random number generator must be verifiable and reproducible throughout the concurrent execution. We propose a family of vectorized Permuted Congruential Generators. Implementations are available for multiple modern vector modern computer architectures. Besides demonstrating good single core performance, the generators scale easily across many processor cores and multiple distributed nodes. We provide performance and parallel speedup analysis and comparisons between the implementations.

Keywords: pseudo-random numbers, quantum optimization, SIMD, parallel computing

Procedia PDF Downloads 118
2681 Quality Assurances for an On-Board Imaging System of a Linear Accelerator: Five Months Data Analysis

Authors: Liyun Chang, Cheng-Hsiang Tsai

Abstract:

To ensure the radiation precisely delivering to the target of cancer patients, the linear accelerator equipped with the pretreatment on-board imaging system is introduced and through it the patient setup is verified before the daily treatment. New generation radiotherapy using beam-intensity modulation, usually associated the treatment with steep dose gradients, claimed to have achieved both a higher degree of dose conformation in the targets and a further reduction of toxicity in normal tissues. However, this benefit is counterproductive if the beam is delivered imprecisely. To avoid shooting critical organs or normal tissues rather than the target, it is very important to carry out the quality assurance (QA) of this on-board imaging system. The QA of the On-Board Imager® (OBI) system of one Varian Clinac-iX linear accelerator was performed through our procedures modified from a relevant report and AAPM TG142. Two image modalities, 2D radiography and 3D cone-beam computed tomography (CBCT), of the OBI system were examined. The daily and monthly QA was executed for five months in the categories of safety, geometrical accuracy and image quality. A marker phantom and a blade calibration plate were used for the QA of geometrical accuracy, while the Leeds phantom and Catphan 504 phantom were used in the QA of radiographic and CBCT image quality, respectively. The reference images were generated through a GE LightSpeed CT simulator with an ADAC Pinnacle treatment planning system. Finally, the image quality was analyzed via an OsiriX medical imaging system. For the geometrical accuracy test, the average deviations of the OBI isocenter in each direction are less than 0.6 mm with uncertainties less than 0.2 mm, while all the other items have the displacements less than 1 mm. For radiographic image quality, the spatial resolution is 1.6 lp/cm with contrasts less than 2.2%. The spatial resolution, low contrast, and HU homogenous of CBCT are larger than 6 lp/cm, less than 1% and within 20 HU, respectively. All tests are within the criteria, except the HU value of Teflon measured with the full fan mode exceeding the suggested value that could be due to itself high HU value and needed to be rechecked. The OBI system in our facility was then demonstrated to be reliable with stable image quality. The QA of OBI system is really necessary to achieve the best treatment for a patient.

Keywords: CBCT, image quality, quality assurance, OBI

Procedia PDF Downloads 297
2680 Hybrid Thresholding Lifting Dual Tree Complex Wavelet Transform with Wiener Filter for Quality Assurance of Medical Image

Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

Abstract:

The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

Procedia PDF Downloads 162
2679 Day/Night Detector for Vehicle Tracking in Traffic Monitoring Systems

Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

Abstract:

Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring

Procedia PDF Downloads 554
2678 Structural and Optoelectronic Properties of Monovalent Cation Doping PbS Thin Films

Authors: Melissa Chavez Portillo, Hector Juarez Santiesteban, Mauricio Pacio Castillo, Oscar Portillo Moreno

Abstract:

Nanocrystalline Li-doped PbS thin films have been deposited by chemical bath deposition technique. The goal of this work is to study the modification of the optoelectronic and structural properties of Lithium incorporation. The increase of Li doping in PbS thin films leads to an increase of band gap in the range of 1.4-2.3, consequently, quantum size effect becomes pronounced in the Li-doped PbS films, which lead to a significant enhancement in the optical band gap. Doping shows influence in the film growth and results in a reduction of crystallite size from 30 to 14 nm. The refractive index was calculated and a relationship with dielectric constant was investigated. The dc conductivities of Li-doped and undoped samples were measured in the temperature range 290-340K, the conductivity increase with increase of Lithium content in the PbS films.

Keywords: doping, quantum confinement, optical band gap, PbS

Procedia PDF Downloads 381