Pub Date : 2010-07-07DOI: 10.1109/IPTA.2010.5586767
K. Boukharouba, L. Bako, S. Lecoeuche
The analysis of digital video content is of fundamental importance for efficient browsing, indexing and retrieval of video database in order to facilitate user's access to relevant data. An essential first step is the parsing of the video content into visually-coherent segments, called shots. In this paper we propose an efficient approach for shot change detection and shot modeling based on a new Switched AutoRegressive (SAR) model identification technique. We make the assumption that pixel intensities of all the frames obey a SAR model where each linear sub-model of the SAR model corresponds to a shot and each discrete state corresponds to a different event in the video. Finally, experimental results on three different video sequences show the performance and the feasibility of the proposed approach.
{"title":"Temporal video segmentation using a switched affine models identification technique","authors":"K. Boukharouba, L. Bako, S. Lecoeuche","doi":"10.1109/IPTA.2010.5586767","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586767","url":null,"abstract":"The analysis of digital video content is of fundamental importance for efficient browsing, indexing and retrieval of video database in order to facilitate user's access to relevant data. An essential first step is the parsing of the video content into visually-coherent segments, called shots. In this paper we propose an efficient approach for shot change detection and shot modeling based on a new Switched AutoRegressive (SAR) model identification technique. We make the assumption that pixel intensities of all the frames obey a SAR model where each linear sub-model of the SAR model corresponds to a shot and each discrete state corresponds to a different event in the video. Finally, experimental results on three different video sequences show the performance and the feasibility of the proposed approach.","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":"122955041","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.2010.5586789
M. Rubeaux, Jean-Claude Nunes, L. Albera, M. Garreau
Mutual Information (MI) has been extensively used as a similarity measure in image registration and motion estimation, and it is particularly robust for 3D multimodal medical image registration. However, MI estimators are known i) to have a high variance and ii) to be computationally costly. In order to overcome these drawbacks, we propose a new similarity measure based on an Edgeworth-based third order expansion of MI and named 3-EMI in the following. This kind of approximation is well known in signal processing, and especially in Independent Components Analysis (ICA), but its computation is easier since data can be prewhitened contrary to images in registration. The performance of affine and non-rigid registrations based on the 3-EMI metric is studied through computer results in the context of cardiac multislice computed tomography. In fact, an estimate of the 3-EMI metric using sample statistics is compared to a histogram-based estimate of the standard normalized MI, showing a better robustness of the 3-EMI measure with respect to the range of the searched deformation. In addition, in practice, one part of the floating image may be missing regarding the reference image. Computer results show that our approach is less sensitive to such a practical problem.
{"title":"Edgeworth-based approximation of Mutual Information for medical image registration","authors":"M. Rubeaux, Jean-Claude Nunes, L. Albera, M. Garreau","doi":"10.1109/IPTA.2010.5586789","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586789","url":null,"abstract":"Mutual Information (MI) has been extensively used as a similarity measure in image registration and motion estimation, and it is particularly robust for 3D multimodal medical image registration. However, MI estimators are known i) to have a high variance and ii) to be computationally costly. In order to overcome these drawbacks, we propose a new similarity measure based on an Edgeworth-based third order expansion of MI and named 3-EMI in the following. This kind of approximation is well known in signal processing, and especially in Independent Components Analysis (ICA), but its computation is easier since data can be prewhitened contrary to images in registration. The performance of affine and non-rigid registrations based on the 3-EMI metric is studied through computer results in the context of cardiac multislice computed tomography. In fact, an estimate of the 3-EMI metric using sample statistics is compared to a histogram-based estimate of the standard normalized MI, showing a better robustness of the 3-EMI measure with respect to the range of the searched deformation. In addition, in practice, one part of the floating image may be missing regarding the reference image. Computer results show that our approach is less sensitive to such a practical problem.","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":"131326396","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.2010.5586786
Adel Almohammad, G. Ghinea
Digital image steganography is the art of hiding information in other digital images. Moreover, image quality evaluation has many difficulties such as the amount of degradation or distortion induced in the reconstructed image. The peak signal-to-noise ratio (PSNR) is the most common metric used to evaluate the stego image quality. However, subjective evaluation is the most reliable method to measure the image quality. Therefore, we try to give an answer to the following question: “does the PSNR value of a stego image reflect its actual quality?”. However, JPEG steganography represents a distortion source in addition to the image compression. Therefore, this paper investigates the relationship, if there any, between the PSNR and the subjective quality of stego images. Four steganography methods and five grayscale images are used in this paper. Moreover, an adapted double stimulus continuous quality scale (DSCQS) method has been adopted. As a result, PSNR can not be reliably used because it has poor correlation with the mean opinion score (MOS). Moreover, conclusions derived from only PSNR values of different stego images are quite different from that derived from the MOS values. Additionally, MOS shows that a particular steganography method modifies different test images quality in different ways.
{"title":"Stego image quality and the reliability of PSNR","authors":"Adel Almohammad, G. Ghinea","doi":"10.1109/IPTA.2010.5586786","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586786","url":null,"abstract":"Digital image steganography is the art of hiding information in other digital images. Moreover, image quality evaluation has many difficulties such as the amount of degradation or distortion induced in the reconstructed image. The peak signal-to-noise ratio (PSNR) is the most common metric used to evaluate the stego image quality. However, subjective evaluation is the most reliable method to measure the image quality. Therefore, we try to give an answer to the following question: “does the PSNR value of a stego image reflect its actual quality?”. However, JPEG steganography represents a distortion source in addition to the image compression. Therefore, this paper investigates the relationship, if there any, between the PSNR and the subjective quality of stego images. Four steganography methods and five grayscale images are used in this paper. Moreover, an adapted double stimulus continuous quality scale (DSCQS) method has been adopted. As a result, PSNR can not be reliably used because it has poor correlation with the mean opinion score (MOS). Moreover, conclusions derived from only PSNR values of different stego images are quite different from that derived from the MOS values. Additionally, MOS shows that a particular steganography method modifies different test images quality in different ways.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"17 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":"125505485","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.2010.5586792
Y. Dhome, N. Tronson, A. Vacavant, T. Chateau, C. Gabard, Y. Goyat, D. Gruyer
Background subtraction of video sequences is mainly regarded as a solved problem. However, no complete benchmark about Background Subtraction Algorithms (BSA) has been established, with ground truth and associated quality measures. One of the reasons is that such comparative study needs annotated datasets. In this article, we propose a BSA evaluation dataset built from realistic synthetic image and we compare six BSA, according to several quality measures.
{"title":"A benchmark for Background Subtraction Algorithms in monocular vision: A comparative study","authors":"Y. Dhome, N. Tronson, A. Vacavant, T. Chateau, C. Gabard, Y. Goyat, D. Gruyer","doi":"10.1109/IPTA.2010.5586792","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586792","url":null,"abstract":"Background subtraction of video sequences is mainly regarded as a solved problem. However, no complete benchmark about Background Subtraction Algorithms (BSA) has been established, with ground truth and associated quality measures. One of the reasons is that such comparative study needs annotated datasets. In this article, we propose a BSA evaluation dataset built from realistic synthetic image and we compare six BSA, according to several quality measures.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"40 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":"124711124","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.2010.5586724
E. R. C. Morales, Yosu Yurramendi Mendizabal
Traditional clustering methods do not take into account any relations possibly present in data. This paper introduces a contiguity-constrained algorithm with an aggregation index which uses neighbouring relations present in the data. Experiments show the behaviour of the proposed method in the case of medical image segmentation.
{"title":"Contiguity-constrained hierarchical clustering for image segmentation","authors":"E. R. C. Morales, Yosu Yurramendi Mendizabal","doi":"10.1109/IPTA.2010.5586724","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586724","url":null,"abstract":"Traditional clustering methods do not take into account any relations possibly present in data. This paper introduces a contiguity-constrained algorithm with an aggregation index which uses neighbouring relations present in the data. Experiments show the behaviour of the proposed method in the case of medical image segmentation.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"45 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120812824","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.2010.5586804
D. Rosario, J. Romano
This paper presents a unique multidimensional image processing approach for autonomous detection of anomalous materials in unknown natural clutter scenarios. Scene anomaly detection has a wide range of use in remote sensing applications requiring no specific material signatures. The approach uses a repeated multisampling scheme to characterize the unknown clutter background and the most popular anomaly detection algorithm—the Reed-Xiaoli algorithm—for scoring. The approach requires only a small fraction of the data cube to characterize clutter, it does not perform segmentation, and it is invariant to objects' scales (i.e., relative spatial sizes of objects in the imagery). Results using real multivariate spectral data are promising for autonomous manmade object detection tasks under different atmospheric conditions.
{"title":"Multidimensional image processing for remote sensing anomaly detection","authors":"D. Rosario, J. Romano","doi":"10.1109/IPTA.2010.5586804","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586804","url":null,"abstract":"This paper presents a unique multidimensional image processing approach for autonomous detection of anomalous materials in unknown natural clutter scenarios. Scene anomaly detection has a wide range of use in remote sensing applications requiring no specific material signatures. The approach uses a repeated multisampling scheme to characterize the unknown clutter background and the most popular anomaly detection algorithm—the Reed-Xiaoli algorithm—for scoring. The approach requires only a small fraction of the data cube to characterize clutter, it does not perform segmentation, and it is invariant to objects' scales (i.e., relative spatial sizes of objects in the imagery). Results using real multivariate spectral data are promising for autonomous manmade object detection tasks under different atmospheric conditions.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"9 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":"128877826","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.2010.5586775
R. Javidan
In almost any underwater operation that takes place on or under the seafloor, it is necessary to have an understanding of the makeup of the seabed below the silt and sediment. Sonar is an acoustic system extensively used for underwater inspection as well as seabed classification. In this paper, the problem of automatic segmentation and classification of seafloor using automatic acoustic seabed discrimination systems is discussed and a new split and merge algorithm based on the concept of standard wavelet transform is presented. Experimental results on true prototype data indicate the robustness and effectiveness of the proposed algorithm.
{"title":"Wavelet-based acoustic seabed discrimination system","authors":"R. Javidan","doi":"10.1109/IPTA.2010.5586775","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586775","url":null,"abstract":"In almost any underwater operation that takes place on or under the seafloor, it is necessary to have an understanding of the makeup of the seabed below the silt and sediment. Sonar is an acoustic system extensively used for underwater inspection as well as seabed classification. In this paper, the problem of automatic segmentation and classification of seafloor using automatic acoustic seabed discrimination systems is discussed and a new split and merge algorithm based on the concept of standard wavelet transform is presented. Experimental results on true prototype data indicate the robustness and effectiveness of the proposed algorithm.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"7 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":"127615916","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.2010.5586781
J. Guédon, Chuanlin Liu
Discrete tomography generally focus on binary image reconstruction from two projections. The Mojette transform allows for a more general framework with any kind of values and any number of projections. Here we use the Mojette transform to address the problem of the 3 materials reconstruction. A new Mojette algorithm is derived and presented in the case of sparse data (reduce number of projections). This algorithm is also generalized for different other uses as for a binary scene reconstruction.
{"title":"The 2 and 3 materials scene reconstructed from some line Mojette projections","authors":"J. Guédon, Chuanlin Liu","doi":"10.1109/IPTA.2010.5586781","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586781","url":null,"abstract":"Discrete tomography generally focus on binary image reconstruction from two projections. The Mojette transform allows for a more general framework with any kind of values and any number of projections. Here we use the Mojette transform to address the problem of the 3 materials reconstruction. A new Mojette algorithm is derived and presented in the case of sparse data (reduce number of projections). This algorithm is also generalized for different other uses as for a binary scene reconstruction.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"51 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":"132020425","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.2010.5586782
K. Messaoudi, E. Bourennane, S. Toumi, E. Kerkouche, Ouassila Labbani
In this paper, we propose a real-time platform for the H.264 CODEC with a memory management method, in which we use a preloading mechanism in order to reduce access to external memory. The platform uses an external DDR2 memory (to record the sequence images) and an intelligent memory controller to read the external memory periodically to load another local memory by the macroblocks (of different sizes) for the processing modules of the H.264 encoder, depending on image manipulation and chosen processing mode. The proposed intelligent controller is tested on a Xilinx virtex5-ML501 platform with multiple internal and external components, including a DDR2 memory. Similarly, the proposed memory controller is well adapted to future System-on-Chip applications with restricted memory-bandwidth.
{"title":"Memory requirements and simulation platform for the implementation of the H.264 encoder modules","authors":"K. Messaoudi, E. Bourennane, S. Toumi, E. Kerkouche, Ouassila Labbani","doi":"10.1109/IPTA.2010.5586782","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586782","url":null,"abstract":"In this paper, we propose a real-time platform for the H.264 CODEC with a memory management method, in which we use a preloading mechanism in order to reduce access to external memory. The platform uses an external DDR2 memory (to record the sequence images) and an intelligent memory controller to read the external memory periodically to load another local memory by the macroblocks (of different sizes) for the processing modules of the H.264 encoder, depending on image manipulation and chosen processing mode. The proposed intelligent controller is tested on a Xilinx virtex5-ML501 platform with multiple internal and external components, including a DDR2 memory. Similarly, the proposed memory controller is well adapted to future System-on-Chip applications with restricted memory-bandwidth.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"47 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":"133007964","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.2010.5586763
B. Presles, J. Debayle, A. Cameirao, G. Févotte, J. Pinoli
The aim of this article is to present a new projective stereological image processing method to estimate the volume of a 3D particle with known convex shape from its different projected areas. In order to do so, an optimization algorithm is performed to determine the size parameters of the particle which maximize the likelihood function of the probability density associated with the observed projected areas. Therefore, the volume of the 3D particle can be deduced.
{"title":"Volume estimation of 3D particles with known convex shapes from its projected areas","authors":"B. Presles, J. Debayle, A. Cameirao, G. Févotte, J. Pinoli","doi":"10.1109/IPTA.2010.5586763","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586763","url":null,"abstract":"The aim of this article is to present a new projective stereological image processing method to estimate the volume of a 3D particle with known convex shape from its different projected areas. In order to do so, an optimization algorithm is performed to determine the size parameters of the particle which maximize the likelihood function of the probability density associated with the observed projected areas. Therefore, the volume of the 3D particle can be deduced.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"59 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":"133273574","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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