Search results for: vision aided INS

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

Procedia PDF Downloads 75

Authors: Valencia P. L. Rodrigo, Morita A. Adelina, Vargas V. Martin

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This proposal consists of an analysis of macro concepts involved within an organization growth using educational technologies, which will relate each concept, in a mathematical way with a vision of harmonic work. Working collaboratively, competitively and cooperatively so that this growth is harmonious and homogenous, coining a new term, Harmonic Work. The Harmonic Work ensures that the organization grows in all business directions, allowing managers to project a much more accurate growth, making clear the contribution of each department, resulting in an algorithm that analyzes each of the variables both endogenous and exogenous, establishing different performance indicators in its process of growth.

Keywords: business projection, collaboration, competitiveness, educational technology, harmonious growth

Procedia PDF Downloads 297

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

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This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 187

Authors: G. Kermarrec, J. Hartmann

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Spline surfaces are a major representation of freeform surfaces in the computer-aided graphic industry and were recently introduced in the field of geodesy for processing point clouds from terrestrial laser scanner (TLS). The surface fitting consists of approximating a trustworthy mathematical surface to a large numbered 3D point cloud. The standard B-spline surfaces lack of local refinement due to the tensor-product construction. The consequences are oscillating geometry, particularly in the transition from low-to-high curvature parts for scattered point clouds with missing data. More economic alternatives in terms of parameters on how to handle point clouds with a huge amount of observations are the recently introduced T-splines. As long as the partition of unity is guaranteed, their computational complexity is low, and they are flexible. T-splines are implemented in a commercial package called Rhino, a 3D modeler which is widely used in computer aided design to create and animate NURBS objects. We have applied T-splines surface fitting to terrestrial laser scanner point clouds from a bridge under load and a sheet pile wall with noisy observations. We will highlight their potential for modelling details with high trustworthiness, paving the way for further applications in terms of deformation analysis.

Keywords: deformation analysis, surface modelling, terrestrial laser scanner, T-splines

Procedia PDF Downloads 121

Authors: Nurtekin Erkmen, Turgut Kaplan, Halil Taskin, Ahmet Sanioglu, Gokhan Ipekoglu

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The aim of this study was to determine the effects of an 8 week soccerspecific technical training with limited vision perception on postural control and technical parameters in 10-12 aged soccer players. Subjects in this study were 24 male young soccer players (age: 11.00 ± 0.56 years, height: 150.5 ± 4.23 cm, body weight: 41.49 ± 7.56 kg). Subjects were randomly divided as two groups: Training and control. Balance performance was measured by Biodex Balance System (BBS). Short pass, speed dribbling, 20 m speed with ball, ball control, juggling tests were used to measure soccer players’ technical performances with a ball. Subjects performed soccer training 3 times per week for 8 weeks. In each session, training group with limited vision perception and control group with normal vision perception committed soccer-specific technical drills for 20 min. Data analyzed with t-test for independent samples and Mann-Whitney U between groups and paired t-test and Wilcoxon test between pre-posttests. No significant difference was found balance scores and with eyes open and eyes closed and LOS test between training and control groups after training (p>0.05). After eight week of training there are no significant difference in balance score with eyes open for both training and control groups (p>0.05). Balance scores decreased in training and control groups after the training (p<0.05). The completion time of LOS test shortened in both training and control groups after training (p<0.05). The training developed speed dribbling performance of training group (p<0.05). On the other hand, soccer players’ performance in training and control groups increased in 20 m speed with a ball after eight week training (p<0.05). In conclusion; the results of this study indicate that soccer-specific training with limited vision perception may not improves balance performance in 10-12 aged soccer players, but it develops speed dribbling performance.

Keywords: Young soccer players, vision perception, postural control, technical

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Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: hard turning, computer aided engineering, computational machining, finite element method

Procedia PDF Downloads 436

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

Abstract:

This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 216

Authors: Joel Carlos Vieira Reinhardt, Mariana de Freitas Dewes, Odair Lelis Gonçalez

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This paper proposes a method to implement a strategic framework for the quality management system that considers the analysis of prospective scenarios in the determination of policy, mission, vision, objectives, processes, monitoring, and goals. Semantic categorization of qualitative testimonial research on employee perception shows it was possible to implement an effective change in the organizations at the Department of Aerospace Science and Technology through the focus on the organization's needs management, producing a rupture with the historical managerial practice.

Keywords: management of company needs, mission, prospective scenarios, quality management, quality policy, vision

Procedia PDF Downloads 86

Authors: Saeed M. Al Qahtani, Alaa Eldin A. Ayoub

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The study aimed to develop a battery of measures to assessment gifted initiatives in Saudi Arabia. The battery consisted of 17 measures developed in light of Saudi Arabia's future vision objectives for gifted education. A battery was applied to 193 gifted students who benefit from gifted initiatives and programs, 42 teachers of gifted as well as, 40 experts of gifted. Samples were taken from three main regions: Riyadh, Sharqia, Gharbia in Saudi Arabia. The results indicated that battery measures have a reliability and stability index ranging from 0.6 to 0.87. Besides that, results showed that the educational environment lacks many basic components such as facilities, laboratories, and activities that may stimulate creativity and innovation. Furthermore, results showed that there is a weakness in private sector involvement in the construction of educational buildings, special centers for gifted people and the provision of certain facilities that support talented programs. The recommendations of the study indicate the need for the private sector participation in the provision of services and projects for the care of gifted students in Saudi Arabia.

Keywords: battery of measures, gifted care initiatives, Saudi future vision, gifted student

Procedia PDF Downloads 149

Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

Procedia PDF Downloads 296

Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: surface flattening, strain energy, minimum energy, approximate implicit method, fashion design

Procedia PDF Downloads 315

Authors: Dalia El Hadi, Alaa Bou Ghannam, Hala Mostafa, Hana Mansour, Ibrahim Hashim, Soubhi Tahhan, Tharwat El Zahran

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Introduction: Neuro-ophthalmological emergencies require prompt assessment and management to avoid vision or life-threatening sequelae. Some would require neuroimaging. Most commonly used are the CT and MRI of the Brain. They can be over-used when not indicated. Their yield remains dependent on multiple factors relating to the clinical scenario. Methods: A retrospective cross-sectional study was conducted by reviewing the electronic medical records of patients presenting to the Emergency Department (ED) with isolated neuro-ophthalmologic complaints. For each patient, data were collected on the clinical presentation, whether neuroimaging was performed (and which type), and the result of neuroimaging. Analysis of the performed neuroimaging was made, and its yield was determined. Results: A total of 211 patients were reviewed. The complaints or symptoms at presentation were: blurry vision, change in the visual field, transient vision loss, floaters, double vision, eye pain, eyelid droop, headache, dizziness and others such as nausea or vomiting. In the ED, a total of 126 neuroimaging procedures were performed. Ninety-four imagings (74.6%) were normal, while 32 (25.4%) had relevant abnormal findings. Only 2 symptoms were significant for abnormal imaging: blurry vision (p-value= 0.038) and visual field change (p-value= 0.014). While 4 physical exam findings had significant abnormal imaging: visual field defect (p-value= 0.016), abnormal pupil reactivity (p-value= 0.028), afferent pupillary defect (p-value= 0.018), and abnormal optic disc exam (p-value= 0.009). Conclusion: Risk indicators for abnormal neuroimaging in the setting of neuro-ophthalmological emergencies are blurred vision or changes in the visual field on history taking. While visual field irregularities, abnormal pupil reactivity with or without afferent pupillary defect, or abnormal optic discs, are risk factors related to physical testing. These findings, when present, should sway the ED physician towards neuroimaging but still individualizing each case is of utmost importance to prevent time-consuming, resource-draining, and sometimes unnecessary workup. In the end, it suggests a well-structured patient-centered algorithm to be followed by ED physicians.

Keywords: emergency department, neuro-ophthalmology, neuroimaging, risk indicators

Procedia PDF Downloads 154

Authors: Obaid Alotaibi

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Tourism and recreation have become one of the important and influential sectors in most of the modern economies. This sector has been accepted as one of the alternative sources of national income, employment, and foreign exchange. Kuwait has many potentialities in tourism and recreation, and exploitation of this leads to more diversification of the economy besides augmenting its contribution to the GDP. It is an import-oriented economy; it requires hard currencies (foreign exchange) to meet the import costs as well as to maintain stability in the international market. To compensate for the revenue fall stemmed from fluctuations in oil prices -where the agriculture, fisheries, and industrial sectors are too immune and inelastic- the only alternative solution is the regeneration of the tourism and recreation to surface. This study envisages the characteristics of tourism and recreation, the economic and social importance for the society, the physical and human endowments, as well as the tourist pattern and plans for promoting and sustaining tourism in the country. The study summarizes many recommendations, including the necessity of establishing authority or a council for tourism, linking the planning of tourism development with the comprehensive planning for economic and social development in Kuwait in the shadow of 2035 vision, and to encourage the investors to develop new tourist and recreation projects.

Keywords: Kuwait, public-private, partnership, tourism, 2035 vision

Procedia PDF Downloads 102

Authors: Ebtesam Shadadi, Rasha Ibrahim, Essam Ghadafi

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Phishing poses a significant threat as a cybercrime by tricking end users into revealing their confidential and sensitive information. Attackers often manipulate victims to achieve their malicious goals. The increasing prevalence of Phishing has led to extensive research on this issue, including studies focusing on phishing attempts in healthcare institutions in the Kingdom of Saudi Arabia. This paper explores the importance of analyzing phishing attacks, specifically focusing on those targeting the healthcare industry. The study delves into the tactics, obstacles, and remedies associated with these attacks, all while considering the implications for Saudi Vision 2030.

Keywords: phishing, cybersecurity, cyber threat, social engineering, vision 2030

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

Procedia PDF Downloads 278

Authors: Mohammed Alkahtani, Ahmed El-Sherbeeny

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Industrial engineering is among engineering disciplines that have been introduced relatively recently to higher education in Saudi Arabian engineering colleges. The objective of this paper is to shed light on the history and status of IE higher education in different Saudi universities, including statistics comparing student enrollment and graduation in different Saudi public and private universities. This paper then proposes how industrial engineering programs could participate successfully in the Saudi Vision 2030. Finally, the authors show the results of a survey conducted on a number of IE students evaluating various academic and administrative aspects of the IE program at King Saud University.

Keywords: higher education, history, industrial engineering, Vision 2030

Procedia PDF Downloads 297

Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

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Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

Procedia PDF Downloads 132

Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek

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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.

Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking

Procedia PDF Downloads 428

Authors: Gelareh Ghaderi

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the overall objective of this study is to develop two alternative plans of spatial and infrastructural development for the Netwerkstad Twente (Twente region) until 2040 and to assess the impacts of those two alternative plans. This region is located on the eastern border of the Netherlands, and it comprises of five municipalities. Based on the strengths and opportunities of the five municipalities of the Netwerkstad Twente, and in order develop the region internationally, strengthen the job market and retain skilled and knowledgeable young population, two alternative visions have been developed; environmental oriented vision, and economical oriented vision. Environmental oriented vision is based mostly on preserving beautiful landscapes. Twente would be recognized as an educational center, driven by green technologies and environment-friendly economy. Market-oriented vision is based on attracting and developing different economic activities in the region based on visions of the five cities of Netwerkstad Twente, in order to improve the competitiveness of the region in national and international scale. On the basis of the two developed visions and strategies for achieving the visions, land use and infrastructural development are modeled and assessed. Based on the SWOT analysis, criteria were formulated and employed in modeling the two contrasting land use visions by the year 2040. Land use modeling consists of determination of future land use demand, assessment of suitability land (Suitability analysis), and allocation of land uses on suitable land. Suitability analysis aims to determine the available supply of land for future development as well as assessing their suitability for specific type of land uses on the basis of the formulated set of criteria. Suitability analysis was operated using CommunityViz, a Planning Support System application for spatially explicit land suitability and allocation. Netwerkstad Twente has highly developed transportation infrastructure, consists of highways network, national road network, regional road network, street network, local road network, railway network and bike-path network. Based on the assumptions of speed limitations on different types of roads provided, infrastructure accessibility level of predicted land use parcels by four different transport modes is investigated. For evaluation of the two development scenarios, the Multi-criteria Evaluation (MCE) method is used. The first step was to determine criteria used for evaluation of each vision. All factors were categorized as economical, ecological and social. Results of Multi-criteria Evaluation show that Environmental oriented cities scenario has higher overall score. Environment-oriented scenario has impressive scores in relation to economical and ecological factors. This is due to the fact that a large percentage of housing tends towards compact housing. Twente region has immense potential, and the success of this project will define the Eastern part of The Netherlands and create a real competitive local economy with innovations and attractive environment as its backbone.

Keywords: economical oriented vision, environmental oriented vision, infrastructure, land use, multi criteria assesment, vision

Procedia PDF Downloads 207

Authors: Yasser Ahmed Mahmoud Ali Helal

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The use of CAD (Computer Aided Design) technology is ubiquitous in the architecture, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of architecture schools in Nigeria as an important part of the training module. This article examines the ethical issues involved in implementing CAD (Computer Aided Design) content into the architectural education curriculum. Using existing literature, this study begins with the benefits of integrating CAD into architectural education and the responsibilities of different stakeholders in the implementation process. It also examines issues related to the negative use of information technology and the perceived negative impact of CAD use on design creativity. Using a survey method, data from the architecture department of University was collected to serve as a case study on how the issues raised were being addressed. The article draws conclusions on what ensures successful ethical implementation. Millions of people around the world suffer from hepatitis C, one of the world's deadliest diseases. Interferon (IFN) is treatment options for patients with hepatitis C, but these treatments have their side effects. Our research focused on developing an oral small molecule drug that targets hepatitis C virus (HCV) proteins and has fewer side effects. Our current study aims to develop a drug based on a small molecule antiviral drug specific for the hepatitis C virus (HCV). Drug development using laboratory experiments is not only expensive, but also time-consuming to conduct these experiments. Instead, in this in silicon study, we used computational techniques to propose a specific antiviral drug for the protein domains of found in the hepatitis C virus. This study used homology modeling and abs initio modeling to generate the 3D structure of the proteins, then identifying pockets in the proteins. Acceptable lagans for pocket drugs have been developed using the de novo drug design method. Pocket geometry is taken into account when designing ligands. Among the various lagans generated, a new specific for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

Abstract:

Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

Procedia PDF Downloads 53

Authors: They Shao Peng

Abstract:

Machine vision system for inspection is an automated technology that is normally utilized to analyze items on the production line for quality control purposes, it also can be known as an automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws, and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models, which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model, are trained, evaluated, and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage.

Keywords: automated visual inspection, deep learning, machine vision, mobile application

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Authors: Deepika Verma, Runa Sarkar

Abstract:

One of the prominent debates in the social entrepreneurship literature has been to establish whether entrepreneurial work for social well-being by for-profit organizations can be classified as social entrepreneurship or not. Of late, the scholarship has reached a consensus. It concludes that there seems little sense in confining social entrepreneurship to just non-profit organizations. Boosted by this research, increasingly a lot of businesses engaged in filling the social infrastructure gaps in developing countries are calling themselves social enterprise. These organizations are diverse in their ownership, size, objectives, operations and business models. The lack of a comprehensive definition of social enterprise leads to three issues. Firstly, researchers may face difficulty in creating a database for social enterprises because the choice of an entity as a social enterprise becomes subjective or based on some pre-defined parameters by the researcher which is not replicable. Secondly, practitioners who use ‘social enterprise’ in their vision/mission statement(s) may find it difficult to adjust their business models accordingly especially during the times when they face the dilemma of choosing social well-being over business viability. Thirdly, social enterprise and social entrepreneurship attract a lot of donor funding and venture capital. In the paucity of a comprehensive definitional guide, the donors or investors may find assigning grants and investments difficult. It becomes necessary to develop an exhaustive and objective definition of social enterprise and examine whether the understanding of the academicians and practitioners about social enterprise match. This paper develops a dictionary of words often associated with social enterprise or (and) social entrepreneurship. It further compares two lexicographic definitions of social enterprise imputed from the abstracts of academic journal papers and trade publications extracted from the EBSCO database using the ‘tm’ package in R software.

Keywords: EBSCO database, lexicographic definition, social enterprise, text mining

Procedia PDF Downloads 370

Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

Abstract:

Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

Procedia PDF Downloads 170

Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

Procedia PDF Downloads 134

Authors: Sandip Suman

Abstract:

Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 72