Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314235
S. Miah, I. Kaparias, P. Liatsis
Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability. However, cycling is still also perceived as relatively unsafe, and therefore it has yet to be adopted as a real alternative to the private car. Rising accident numbers, unfortunately, confirm this perception as reality, with a particular source of hazard (and a significant proportion of collisions) appearing to originate from the interaction of cyclists with Heavy Vehicles (HVs). For this purpose, the Cyclist 360° Alert system is currently being developed as a novel technological solution aimed at preventing cyclist-HV collisions. As an integral part of Cyclist 360° Alert, this paper focuses on measurements of steering angles using low-cost MEMS sensors based on a motorized two-axis rotational platform. The paper evaluates the accuracy for Tri-axis MEMS inertial sensors and validates the accuracy of the sensors' angles by utilizing an absolute encoder as the reference signal.
{"title":"Evaluation of MEMS sensors accuracy for bicycle tracking and positioning","authors":"S. Miah, I. Kaparias, P. Liatsis","doi":"10.1109/IWSSIP.2015.7314235","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314235","url":null,"abstract":"Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability. However, cycling is still also perceived as relatively unsafe, and therefore it has yet to be adopted as a real alternative to the private car. Rising accident numbers, unfortunately, confirm this perception as reality, with a particular source of hazard (and a significant proportion of collisions) appearing to originate from the interaction of cyclists with Heavy Vehicles (HVs). For this purpose, the Cyclist 360° Alert system is currently being developed as a novel technological solution aimed at preventing cyclist-HV collisions. As an integral part of Cyclist 360° Alert, this paper focuses on measurements of steering angles using low-cost MEMS sensors based on a motorized two-axis rotational platform. The paper evaluates the accuracy for Tri-axis MEMS inertial sensors and validates the accuracy of the sensors' angles by utilizing an absolute encoder as the reference signal.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123598291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314186
Wenli Zhang, Shuangjiu Xiao, Xin Shi
Low-poly has lately become a trending style in flat designs, Web designs, illustrations, and etc., in which only a small amount of triangles are used to provide an abstract and artistic effect. However, creating designs in low-poly style manually is obviously a tiring job. In this paper, we propose a real-time triangulation method to synthesize images and videos automatically into low-poly style. In order to keep edge and color information out of limited triangles, vertices on the edges detected in the image have a greater probability to be selected to compose triangles. For video low-poly stylization, an anti-jittering method is proposed to eliminate the abrupt changes in position and color of the triangles between adjacent frames. We use OpenGL Shading Language (GLSL) to speed up the calculation in GPU. We compare images generated with our method with other algorithms and those drawn manually by artists. Results show that our method provides an elegant and artistic effect for low-poly in real-time.
{"title":"Low-poly style image and video processing","authors":"Wenli Zhang, Shuangjiu Xiao, Xin Shi","doi":"10.1109/IWSSIP.2015.7314186","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314186","url":null,"abstract":"Low-poly has lately become a trending style in flat designs, Web designs, illustrations, and etc., in which only a small amount of triangles are used to provide an abstract and artistic effect. However, creating designs in low-poly style manually is obviously a tiring job. In this paper, we propose a real-time triangulation method to synthesize images and videos automatically into low-poly style. In order to keep edge and color information out of limited triangles, vertices on the edges detected in the image have a greater probability to be selected to compose triangles. For video low-poly stylization, an anti-jittering method is proposed to eliminate the abrupt changes in position and color of the triangles between adjacent frames. We use OpenGL Shading Language (GLSL) to speed up the calculation in GPU. We compare images generated with our method with other algorithms and those drawn manually by artists. Results show that our method provides an elegant and artistic effect for low-poly in real-time.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128652700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a new computer-aided diagnosis (CAD) system for early lung cancer detection based on the analysis of sputum color images is proposed. A set of features is extracted from the nuclei of the sputum cells after applying a region detection process. For training and testing the system we used two classification techniques: artificial neural network (ANN) and support vector machine (SVM) to increase the accuracy of the CAD system. The performance of the system was analyzed based on different criteria such as sensitivity, precision, specificity and accuracy. The evaluation was done by using Receiver Operating Characteristic (ROC) curve. The experimental results demonstrate the efficiency of SVM classifier over the ANN classifier with 97% of sensitivity and accuracy as well as a significant reduction in the number of false positive and false negative rates.
{"title":"Computer aided diagnosis system for early lung cancer detection","authors":"F. Taher, N. Werghi, H. Al-Ahmad","doi":"10.3390/a8041088","DOIUrl":"https://doi.org/10.3390/a8041088","url":null,"abstract":"In this paper, a new computer-aided diagnosis (CAD) system for early lung cancer detection based on the analysis of sputum color images is proposed. A set of features is extracted from the nuclei of the sputum cells after applying a region detection process. For training and testing the system we used two classification techniques: artificial neural network (ANN) and support vector machine (SVM) to increase the accuracy of the CAD system. The performance of the system was analyzed based on different criteria such as sensitivity, precision, specificity and accuracy. The evaluation was done by using Receiver Operating Characteristic (ROC) curve. The experimental results demonstrate the efficiency of SVM classifier over the ANN classifier with 97% of sensitivity and accuracy as well as a significant reduction in the number of false positive and false negative rates.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126269577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314236
S. Miah, Alena Uus, P. Liatsis, Sam Roberts, Stephen Twist, M. Hovens, Hans Godding
This paper presents a systematic approach for decision level sensor fusion of road pavement inspection system under FP7 RPB HealTec- “Road Pavements & Bridge Deck Health Monitoring/Early Warning Using Advanced Inspection Technologies”. The paper focuses on the design aspect of the post processing sensor fusion system and outlines methods that can be used to process and fuse sensor data such as GPR, IRT, ACU and HDV for multidimensional assessment on the road pavement quality condition. In addition, the paper illustrates a visualization technique for mapping of detected defects with road surface and a GIS map.
{"title":"Design of multidimensional sensor fusion system for road pavement inspection","authors":"S. Miah, Alena Uus, P. Liatsis, Sam Roberts, Stephen Twist, M. Hovens, Hans Godding","doi":"10.1109/IWSSIP.2015.7314236","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314236","url":null,"abstract":"This paper presents a systematic approach for decision level sensor fusion of road pavement inspection system under FP7 RPB HealTec- “Road Pavements & Bridge Deck Health Monitoring/Early Warning Using Advanced Inspection Technologies”. The paper focuses on the design aspect of the post processing sensor fusion system and outlines methods that can be used to process and fuse sensor data such as GPR, IRT, ACU and HDV for multidimensional assessment on the road pavement quality condition. In addition, the paper illustrates a visualization technique for mapping of detected defects with road surface and a GIS map.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128142769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314212
Uday Singh Thakur, Olena Chubach
Natural textures like grass, water, sand etc. contain large amount of visual details that consume a lot of bitrate while compressing it, but in fact such details are irrelevant for the human vision. Therefore, exploiting human perception properties could provide better compression of such data. In this paper we propose two novel schemes for identifying and processing static and dynamic textures based on 2D Dual Tree Complex Wavelet Transform and Steerable Pyramid Transform. The use of Steerable Filters is motivated by the fact that the frequency and directional selectivity of the Human Visual System can be well modelled by the Steerable Filters.
{"title":"Texture analysis and synthesis using steerable pyramid decomposition for video coding","authors":"Uday Singh Thakur, Olena Chubach","doi":"10.1109/IWSSIP.2015.7314212","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314212","url":null,"abstract":"Natural textures like grass, water, sand etc. contain large amount of visual details that consume a lot of bitrate while compressing it, but in fact such details are irrelevant for the human vision. Therefore, exploiting human perception properties could provide better compression of such data. In this paper we propose two novel schemes for identifying and processing static and dynamic textures based on 2D Dual Tree Complex Wavelet Transform and Steerable Pyramid Transform. The use of Steerable Filters is motivated by the fact that the frequency and directional selectivity of the Human Visual System can be well modelled by the Steerable Filters.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133733485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314210
Anfisa Lazareva, P. Liatsis, F. Rauscher
This paper presents an automated image processing framework for facilitating the accurate detection of photoreceptor cells. The performance of the proposed method was evaluated in terms of cone density calculated on synthetic and high-resolution retinal images. The validation study on the synthetic data showed an average accuracy of 98.8% for the proposed method in comparison with 93.9% obtained by the Li and Roorda algorithm. The cone density calculated on the high-resolution retinal images demonstrated satisfactory agreement with the histological data as well as previously published data on photoreceptor packing density at a given location.
{"title":"An automated image processing system for the detection of photoreceptor cells in adaptive optics retinal images","authors":"Anfisa Lazareva, P. Liatsis, F. Rauscher","doi":"10.1109/IWSSIP.2015.7314210","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314210","url":null,"abstract":"This paper presents an automated image processing framework for facilitating the accurate detection of photoreceptor cells. The performance of the proposed method was evaluated in terms of cone density calculated on synthetic and high-resolution retinal images. The validation study on the synthetic data showed an average accuracy of 98.8% for the proposed method in comparison with 93.9% obtained by the Li and Roorda algorithm. The cone density calculated on the high-resolution retinal images demonstrated satisfactory agreement with the histological data as well as previously published data on photoreceptor packing density at a given location.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132024517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314225
M. Al-Qahtani, A. Amira, N. Ramzan
In the health domain, the adoption of computer systems introduces better services, reduces human errors, and provides reliable services with nearly zero down time. In general, data in computer systems is stored in coded format; however, certain data, like user comments, cannot be coded. Hence, it is stored in the form of free text. Based on the results of the performed literature review, it was identified that the free text contains invaluable information; however, extracting such information is a challenging task due to the complexity of the stored data. In this paper, a Latent Semantic Indexing (LSI) algorithm is developed and applied on The Health Improvement Network (THIN). The algorithm utilizes the computational power provided by the multi-processor/multi-core system in performing the IR process. Further to that, the paper investigates the representation of the patient's data in the Term Document Matrix (TDM) to enhance the accuracy of the retrieved information.
{"title":"An efficient information retrieval technique for e-health systems","authors":"M. Al-Qahtani, A. Amira, N. Ramzan","doi":"10.1109/IWSSIP.2015.7314225","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314225","url":null,"abstract":"In the health domain, the adoption of computer systems introduces better services, reduces human errors, and provides reliable services with nearly zero down time. In general, data in computer systems is stored in coded format; however, certain data, like user comments, cannot be coded. Hence, it is stored in the form of free text. Based on the results of the performed literature review, it was identified that the free text contains invaluable information; however, extracting such information is a challenging task due to the complexity of the stored data. In this paper, a Latent Semantic Indexing (LSI) algorithm is developed and applied on The Health Improvement Network (THIN). The algorithm utilizes the computational power provided by the multi-processor/multi-core system in performing the IR process. Further to that, the paper investigates the representation of the patient's data in the Term Document Matrix (TDM) to enhance the accuracy of the retrieved information.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128281094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7313931
Karam Naser, V. Ricordel, P. Callet
Textures are one of the main characteristics of the visual scene. Perceptually, their details are less important than their semantic meaning. This property has been exploited in many texture coding (content based video coding) approaches by removing parts of the textures in the encoder and synthesizing them at the decoder side. Such an approach would necessarily need modification of the coding process and violating the standard. This paper introduces a novel algorithm for texture coding called Local Texture Synthesis (LTS), in which texture synthesis is employed in a full compatibility with HEVC standard. This implies that a basic HEVC decoder can be used to reconstruct the signal. LTS defines the necessary conditions to synthesize a patch and produces different synthesis of it. It tries then coding each of them, and finally chooses the one that minimizes the coding cost. A prototype of this algorithm, based on Markov Random Fields, is given in this paper. This prototype provides up to 10% bitrate saving (using the same quantization parameter) while maintaining an equivalent visual quality.
{"title":"Local texture synthesis: A static texture coding algorithm fully compatible with HEVC","authors":"Karam Naser, V. Ricordel, P. Callet","doi":"10.1109/IWSSIP.2015.7313931","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7313931","url":null,"abstract":"Textures are one of the main characteristics of the visual scene. Perceptually, their details are less important than their semantic meaning. This property has been exploited in many texture coding (content based video coding) approaches by removing parts of the textures in the encoder and synthesizing them at the decoder side. Such an approach would necessarily need modification of the coding process and violating the standard. This paper introduces a novel algorithm for texture coding called Local Texture Synthesis (LTS), in which texture synthesis is employed in a full compatibility with HEVC standard. This implies that a basic HEVC decoder can be used to reconstruct the signal. LTS defines the necessary conditions to synthesize a patch and produces different synthesis of it. It tries then coding each of them, and finally chooses the one that minimizes the coding cost. A prototype of this algorithm, based on Markov Random Fields, is given in this paper. This prototype provides up to 10% bitrate saving (using the same quantization parameter) while maintaining an equivalent visual quality.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125716162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314181
Jie Shao, Nan Dong, Qian Zhao
Collective motion groups play an important role in pedestrian crowd analysis and social event detection. As the basis of group modeling in the crowd, a collective motion group detection algorithm is proposed in this paper. Compared to other state-of-the-art group detection achievements, ours is more robust in complex crowded motion scenes, involving varieties of random traffics and different motion types. First of all, we introduce an automatic foreground detection strategy, and then generate dense tracklets by tracking on salient points in foreground area for preprocessing. Salient point tracklets are represented by spatio-temporal features afterwards. By exploiting an adaptive initiation clustering technique, a hierarchical clustering model is built to partition the crowd into groups depending on different features layer by layer. We demonstrate the effectiveness and robustness of our algorithm quantitatively and qualitatively on various real crowd videos.
{"title":"An adaptive clustering approach for group detection in the crowd","authors":"Jie Shao, Nan Dong, Qian Zhao","doi":"10.1109/IWSSIP.2015.7314181","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314181","url":null,"abstract":"Collective motion groups play an important role in pedestrian crowd analysis and social event detection. As the basis of group modeling in the crowd, a collective motion group detection algorithm is proposed in this paper. Compared to other state-of-the-art group detection achievements, ours is more robust in complex crowded motion scenes, involving varieties of random traffics and different motion types. First of all, we introduce an automatic foreground detection strategy, and then generate dense tracklets by tracking on salient points in foreground area for preprocessing. Salient point tracklets are represented by spatio-temporal features afterwards. By exploiting an adaptive initiation clustering technique, a hierarchical clustering model is built to partition the crowd into groups depending on different features layer by layer. We demonstrate the effectiveness and robustness of our algorithm quantitatively and qualitatively on various real crowd videos.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132211041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-02DOI: 10.1109/IWSSIP.2015.7314189
O. P. S. Neto, O. Carvalho, W. B. Sampaio, A. Silva, A. Paiva
This paper presents a methodology for automatic segmentation of masses in digital mammograms based on two principles: thresholding and evolutionary algorithm. As the staring point of the particles of the swarm, we used Otsu. Then, we applied the Particle Swarm Optimization (PSO) to optimize, evolutionarily, the search for the global maximum of the thresholds in order to achieve a better segmentation. After the segmentation stage, we executed a reduction of false positives based on region growing, area filter and Graph Clustering.
{"title":"Automatic segmentation of masses in digital mammograms using particle swarm optimization and graph clustering","authors":"O. P. S. Neto, O. Carvalho, W. B. Sampaio, A. Silva, A. Paiva","doi":"10.1109/IWSSIP.2015.7314189","DOIUrl":"https://doi.org/10.1109/IWSSIP.2015.7314189","url":null,"abstract":"This paper presents a methodology for automatic segmentation of masses in digital mammograms based on two principles: thresholding and evolutionary algorithm. As the staring point of the particles of the swarm, we used Otsu. Then, we applied the Particle Swarm Optimization (PSO) to optimize, evolutionarily, the search for the global maximum of the thresholds in order to achieve a better segmentation. After the segmentation stage, we executed a reduction of false positives based on region growing, area filter and Graph Clustering.","PeriodicalId":249021,"journal":{"name":"2015 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125448289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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