Pub Date : 2010-07-07DOI: 10.1109/IPTA.2010.5586742
Tae-Woo Oh, Kyung-Su Kim, Hae-Yeoun Lee, Ji Won Lee, Heung-Kyu Lee
This paper proposes a composite mask based watermarking method, which improves perceptual quality of videos watermarked by traditional video watermarking scheme. The composite mask including noise visibility function (NVF) mask, adaptive dithering mask, and contour mask considers human visual system (HVS). The adaptive dithering mask solves the block artifact problem caused by expanding the watermark basic pattern for the robustness against various downscaling attacks. The contour mask makes up for the disadvantage of NVF mask, which cannot handle separately high textured regions and contour or edge regions. Extensive experiments prove that the watermarking method based on the proposed composite mask satisfies imperceptibility, robustness against downscaling as well as common video processing, and real-time performance.
{"title":"Enhancing perceptual quality of watermarked high-definition video through composite mask","authors":"Tae-Woo Oh, Kyung-Su Kim, Hae-Yeoun Lee, Ji Won Lee, Heung-Kyu Lee","doi":"10.1109/IPTA.2010.5586742","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586742","url":null,"abstract":"This paper proposes a composite mask based watermarking method, which improves perceptual quality of videos watermarked by traditional video watermarking scheme. The composite mask including noise visibility function (NVF) mask, adaptive dithering mask, and contour mask considers human visual system (HVS). The adaptive dithering mask solves the block artifact problem caused by expanding the watermark basic pattern for the robustness against various downscaling attacks. The contour mask makes up for the disadvantage of NVF mask, which cannot handle separately high textured regions and contour or edge regions. Extensive experiments prove that the watermarking method based on the proposed composite mask satisfies imperceptibility, robustness against downscaling as well as common video processing, and real-time performance.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130235623","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586754
M. Saad, A. Alimi
This paper presents a study on the fuzzy classification techniques that have been applied to the MR images. The goal is to improve the fuzzy techniques in inventing a new classification method, called the Improved Modified Suppressed Fuzzy C-Means (IMS-FCM) which modifies another algorithm called Modified Suppressed Fuzzy C-Means (MS-FCM). The latter one works with a common parameter α based on the exponential separation strength between clusters in each iteration in order to modify the memberships degrees of the pixels and to accelerate in consequence the convergence of the standard algorithm FCM to the optimum. It's not logical because the context differs from one pixel to another. To overcome this disadvantage we propose a new version of MS-FCM taking account of noise aspect. The former aspect is treated by a new parameter called the degree of cleanness of the pixel relatively to a class instead of α. We test the new algorithm and the FCM, S-FCM and MS-FCM algorithms in many magnetic resonance images. Overall, the new algorithm gives better results than the others.
{"title":"Improved Modified Suppressed Fuzzy C-Means","authors":"M. Saad, A. Alimi","doi":"10.1109/IPTA.2010.5586754","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586754","url":null,"abstract":"This paper presents a study on the fuzzy classification techniques that have been applied to the MR images. The goal is to improve the fuzzy techniques in inventing a new classification method, called the Improved Modified Suppressed Fuzzy C-Means (IMS-FCM) which modifies another algorithm called Modified Suppressed Fuzzy C-Means (MS-FCM). The latter one works with a common parameter α based on the exponential separation strength between clusters in each iteration in order to modify the memberships degrees of the pixels and to accelerate in consequence the convergence of the standard algorithm FCM to the optimum. It's not logical because the context differs from one pixel to another. To overcome this disadvantage we propose a new version of MS-FCM taking account of noise aspect. The former aspect is treated by a new parameter called the degree of cleanness of the pixel relatively to a class instead of α. We test the new algorithm and the FCM, S-FCM and MS-FCM algorithms in many magnetic resonance images. Overall, the new algorithm gives better results than the others.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122392475","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586727
Mohammad Mayya, N. Zarka, M. Alkadi
This paper describes an embedded system for real-time human motion detection using a fixed camera. A modified version of the Codebook algorithm is developed to detect moving objects. This algorithm provides fast background modelling and subtraction with small storage memory requirements. Then, the system detects humans using a simplified Skeletonization algorithm, which uses the individual human shape and does not need a model comparison. Functional and timing simulations are applied by using MATLAB and Visual Studio on PC. Finally, the system is installed on ALTERA Cyclone™ II DSP development board and implemented using the Nios II processor and some hardware accelerators.
{"title":"Embedded system for real-time human motion detection","authors":"Mohammad Mayya, N. Zarka, M. Alkadi","doi":"10.1109/IPTA.2010.5586727","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586727","url":null,"abstract":"This paper describes an embedded system for real-time human motion detection using a fixed camera. A modified version of the Codebook algorithm is developed to detect moving objects. This algorithm provides fast background modelling and subtraction with small storage memory requirements. Then, the system detects humans using a simplified Skeletonization algorithm, which uses the individual human shape and does not need a model comparison. Functional and timing simulations are applied by using MATLAB and Visual Studio on PC. Finally, the system is installed on ALTERA Cyclone™ II DSP development board and implemented using the Nios II processor and some hardware accelerators.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125516080","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586736
Tamim Haroun, F. Labeau
Multiple Hypothesis Motion Compensated Prediction (MHMCP) has been extensively studied and is known to be a very effective method for enhancing the error resilience of motion compensated prediction with little impact on coding efficiency for compressing moving picture sequences. MHMCP with 2 hypotheses (2HMCP) may be used within the H.264/AVC standard by implementing it under the generalized B pictures framework. We explore good implementations of 2HMCP and propose a novel method to further enhance the error resilience by restricting the search areas in each reference frame such that the hypotheses selected from each are not too correlated. We find that there is significant rate-distortion gain, especially for fast moving sequences.
{"title":"Robust Multiple Hypothesis Motion Compensated Prediction within the H.264/AVC standard","authors":"Tamim Haroun, F. Labeau","doi":"10.1109/IPTA.2010.5586736","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586736","url":null,"abstract":"Multiple Hypothesis Motion Compensated Prediction (MHMCP) has been extensively studied and is known to be a very effective method for enhancing the error resilience of motion compensated prediction with little impact on coding efficiency for compressing moving picture sequences. MHMCP with 2 hypotheses (2HMCP) may be used within the H.264/AVC standard by implementing it under the generalized B pictures framework. We explore good implementations of 2HMCP and propose a novel method to further enhance the error resilience by restricting the search areas in each reference frame such that the hypotheses selected from each are not too correlated. We find that there is significant rate-distortion gain, especially for fast moving sequences.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129154052","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586801
V. Fresse, Junyan Tan, F. Rousseau
This paper presents an adaptive communication architecture dedicated to multispectral and hyperspectral imaging algorithms for art authentication for embedded and portable systems. The communication architecture is a Network on Chip (NoC) architecture implemented on a FPGA (Field Programmable Gate Array). From several parameters extracted from the algorithm, an emulation platform is designed to explore performances of the communication architecture. This emulation architecture contains the NoC architecture associated to generator and receptor traffic blocks to simulate data transfers inside the NoC. Several traffic scenarios extracted from the algorithm are explored. Timing and resource performances are analyzed for several parameterizations of the architecture to identify the adapted architecture and their limitations.
{"title":"Exploration of an adaptive NoC architecture on FPGA dedicated to multi and hysperspectral algorithm for art authentication","authors":"V. Fresse, Junyan Tan, F. Rousseau","doi":"10.1109/IPTA.2010.5586801","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586801","url":null,"abstract":"This paper presents an adaptive communication architecture dedicated to multispectral and hyperspectral imaging algorithms for art authentication for embedded and portable systems. The communication architecture is a Network on Chip (NoC) architecture implemented on a FPGA (Field Programmable Gate Array). From several parameters extracted from the algorithm, an emulation platform is designed to explore performances of the communication architecture. This emulation architecture contains the NoC architecture associated to generator and receptor traffic blocks to simulate data transfers inside the NoC. Several traffic scenarios extracted from the algorithm are explored. Timing and resource performances are analyzed for several parameterizations of the architecture to identify the adapted architecture and their limitations.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132828098","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586802
Tara Akhavan, M. Moghaddam
the ability to measure color of objects, independent of color of the light source, is called color constancy which is an important problem in machine vision and image processing. In this paper, we propose a method that employs a neural network to estimate the chromaticity of light source. This network uses the results of four well known color constancy methods as its input in training and tries to find the best result in test phase. In selecting the input methods, it has been tried to select ones which each one focuses on a particular specification of the colored image and is suitable for training also. By considering these issues, Max RGB, gray world assumption, gray edge, and shades of gray as well known methods were selected. In the proposed methods, the result in test phase may correspond with none of these algorithms necessarily. The experimental results showed that the proposed method reached to a good estimation of the illuminant source with less complexity in comparison to the previous related works.
{"title":"A new combining learning method for color constancy","authors":"Tara Akhavan, M. Moghaddam","doi":"10.1109/IPTA.2010.5586802","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586802","url":null,"abstract":"the ability to measure color of objects, independent of color of the light source, is called color constancy which is an important problem in machine vision and image processing. In this paper, we propose a method that employs a neural network to estimate the chromaticity of light source. This network uses the results of four well known color constancy methods as its input in training and tries to find the best result in test phase. In selecting the input methods, it has been tried to select ones which each one focuses on a particular specification of the colored image and is suitable for training also. By considering these issues, Max RGB, gray world assumption, gray edge, and shades of gray as well known methods were selected. In the proposed methods, the result in test phase may correspond with none of these algorithms necessarily. The experimental results showed that the proposed method reached to a good estimation of the illuminant source with less complexity in comparison to the previous related works.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"450 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122888287","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586764
Azhar Hadmi, W. Puech, B. A. E. Said, A. A. Ouahman
Perceptual image hashing maps an image to a fixed length binary string based on the image's appearance to the human eye, and has applications in image indexing, authentication, and watermarking. In this paper, we analyze the robustness of perceptual signatures generated by the known SHA1 hash function in the DWT domain. This is achieved by generation signatures from the coefficients of the subband LL after a DWT transformation. Experiments on large-scale database show that the proposed method is efficient, robust against common content-preserving manipulations.
{"title":"Analysis of the robustness of wavelet-based perceptual signatures","authors":"Azhar Hadmi, W. Puech, B. A. E. Said, A. A. Ouahman","doi":"10.1109/IPTA.2010.5586764","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586764","url":null,"abstract":"Perceptual image hashing maps an image to a fixed length binary string based on the image's appearance to the human eye, and has applications in image indexing, authentication, and watermarking. In this paper, we analyze the robustness of perceptual signatures generated by the known SHA1 hash function in the DWT domain. This is achieved by generation signatures from the coefficients of the subband LL after a DWT transformation. Experiments on large-scale database show that the proposed method is efficient, robust against common content-preserving manipulations.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129230223","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586785
Yuexing Han, H. Koike, Bing Wang, M. Idesawa
Generally, computers can successfully achieve object recognition by relying on sufficient information of observed objects. However, in real world, many objects own diverse configurations or objects are observed at various angles and positions, which make it difficult to match the observed objects with data models in a limited database. In this paper, to resolve the above problem, we propose an algorithm to achieve this kind of object recognition in shape space. Firstly, we describe the algorithm of extracting landmarks from outer contour of a shape by using recursive landmarks determination, in which the number of the landmarks can be appointed. Then, for the objects with many configurations, a series of new data are generated from one or two data models in pre-shape space. Finally, we achieve object recognition with shape space theory. The proposed method is efficient not only for the objects with noises, but also for the ones with various situations.
{"title":"Recognition of objects in various situations from two dimensional images","authors":"Yuexing Han, H. Koike, Bing Wang, M. Idesawa","doi":"10.1109/IPTA.2010.5586785","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586785","url":null,"abstract":"Generally, computers can successfully achieve object recognition by relying on sufficient information of observed objects. However, in real world, many objects own diverse configurations or objects are observed at various angles and positions, which make it difficult to match the observed objects with data models in a limited database. In this paper, to resolve the above problem, we propose an algorithm to achieve this kind of object recognition in shape space. Firstly, we describe the algorithm of extracting landmarks from outer contour of a shape by using recursive landmarks determination, in which the number of the landmarks can be appointed. Then, for the objects with many configurations, a series of new data are generated from one or two data models in pre-shape space. Finally, we achieve object recognition with shape space theory. The proposed method is efficient not only for the objects with noises, but also for the ones with various situations.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115250783","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586723
Luo Juan, O. Gwun
SURF (Speeded Up Robust Features) is one of the famous feature-detection algorithms. This paper proposes a panorama image stitching system which combines an image matching algorithm; modified SURF and an image blending algorithm; multi-band blending. The process is divided in the following steps: first, get feature descriptor of the image using modified SURF; secondly, find matching pairs, check the neighbors by K-NN (K-nearest neighbor), and remove the mismatch couples by RANSAC(Random Sample Consensus); then, adjust the images by bundle adjustment and estimate the accurate homography matrix; lastly, blend images by multi-band blending. Also, comparison of SIFT (Scale Invariant Feature Transform) and modified SURF are also shown as a base of selection of image matching algorithm. According to the experiments, the present system can make the stitching seam invisible and get a perfect panorama for large image data and it is faster than previous method.
{"title":"SURF applied in panorama image stitching","authors":"Luo Juan, O. Gwun","doi":"10.1109/IPTA.2010.5586723","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586723","url":null,"abstract":"SURF (Speeded Up Robust Features) is one of the famous feature-detection algorithms. This paper proposes a panorama image stitching system which combines an image matching algorithm; modified SURF and an image blending algorithm; multi-band blending. The process is divided in the following steps: first, get feature descriptor of the image using modified SURF; secondly, find matching pairs, check the neighbors by K-NN (K-nearest neighbor), and remove the mismatch couples by RANSAC(Random Sample Consensus); then, adjust the images by bundle adjustment and estimate the accurate homography matrix; lastly, blend images by multi-band blending. Also, comparison of SIFT (Scale Invariant Feature Transform) and modified SURF are also shown as a base of selection of image matching algorithm. According to the experiments, the present system can make the stitching seam invisible and get a perfect panorama for large image data and it is faster than previous method.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115657453","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586777
M. Nosrati, Parvaneh Saeedi
Extracting building rooftops in satellite/aerial images is one of the most challenging problems in the application of computer vision for remote sensing. In this paper a new contour propagation model for rooftop boundary detection is proposed. It includes developing contour models that evolve by leaping on image corners and edge points while minimizing an energy function based on image corner responses, image color invariants and edge points. The proposed method is capable for coping with the complications associated with the gabled rooftop using Gaussian color invariance modeling. Experimental results for aerial/satellite images show that the average shape accuracy is above 90% for the test images of sub-urban areas.
{"title":"Rooftop detection using a corner-leaping based contour propagation model","authors":"M. Nosrati, Parvaneh Saeedi","doi":"10.1109/IPTA.2010.5586777","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586777","url":null,"abstract":"Extracting building rooftops in satellite/aerial images is one of the most challenging problems in the application of computer vision for remote sensing. In this paper a new contour propagation model for rooftop boundary detection is proposed. It includes developing contour models that evolve by leaping on image corners and edge points while minimizing an energy function based on image corner responses, image color invariants and edge points. The proposed method is capable for coping with the complications associated with the gabled rooftop using Gaussian color invariance modeling. Experimental results for aerial/satellite images show that the average shape accuracy is above 90% for the test images of sub-urban areas.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121909691","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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