Pub Date : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207432
Yin-Cheng Qi, Liang Ye, Chong Liu
Steganalysis is taken as a countermeasure to steganography and is detecting and decoding hidden data within a given media. There has been quite some effort in audio steganalysis for additive embedding model. However, when they distinguish the cover-audio signal with multiplicative noise and the stego-audio signal, results are disappointing. In this paper, a wavelet domain audio steganalysis method for multiplicative embedding model is proposed. The test audio signal is firstly calculated its absolute value and logarithm. Multiplicative noise is changed to additive noise. Then features are extracted. At last, support vector machine (SVM) is utilized as a classifier to distinguish the cover-audio signal and the stego-audio signal. Simulation results show that the detection rates are greater than 94% and the method is effective.
{"title":"Wavelet domain audio steganalysis for multiplicative embedding model","authors":"Yin-Cheng Qi, Liang Ye, Chong Liu","doi":"10.1109/ICWAPR.2009.5207432","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207432","url":null,"abstract":"Steganalysis is taken as a countermeasure to steganography and is detecting and decoding hidden data within a given media. There has been quite some effort in audio steganalysis for additive embedding model. However, when they distinguish the cover-audio signal with multiplicative noise and the stego-audio signal, results are disappointing. In this paper, a wavelet domain audio steganalysis method for multiplicative embedding model is proposed. The test audio signal is firstly calculated its absolute value and logarithm. Multiplicative noise is changed to additive noise. Then features are extracted. At last, support vector machine (SVM) is utilized as a classifier to distinguish the cover-audio signal and the stego-audio signal. Simulation results show that the detection rates are greater than 94% and the method is effective.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124917069","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207433
Donghui Li
In this paper, we consider the problem of lossless compression of laser speckle images produced in displacement measurement. We propose a lossless compression technique of laser speckle images which is based on speckle displacement estimation, temporal prediction and the Golomb entropy coding. In the proposed coder, the fuzzy-logic-based correlation is used for estimation of speckle displacements. Experimental results show that the proposed coder provides significant improvement in coding efficiency compared with the JPEG_LS coder in compression of laser speckle images.
{"title":"Lossless compression of laser speckle images by the fuzzy logic","authors":"Donghui Li","doi":"10.1109/ICWAPR.2009.5207433","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207433","url":null,"abstract":"In this paper, we consider the problem of lossless compression of laser speckle images produced in displacement measurement. We propose a lossless compression technique of laser speckle images which is based on speckle displacement estimation, temporal prediction and the Golomb entropy coding. In the proposed coder, the fuzzy-logic-based correlation is used for estimation of speckle displacements. Experimental results show that the proposed coder provides significant improvement in coding efficiency compared with the JPEG_LS coder in compression of laser speckle images.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121794771","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207475
Junying Gan, Jun-Feng Liu
In this paper, a novel approach to the fusion and recognition of face and iris image based on wavelet features and Kernel Fisher Discriminant Analysis (KFDA) is developed. Firstly, the dimension is reduced, the noise is eliminated, the storage space is saved and the efficiency is improved by Discrete Wavelet Transform (DWT) to face and iris image. Secondly, face and iris features are extracted and fusion by KFDA. Finally, Nearest Neighbor classifier is selected to perform recognition. Experimental results on ORL face database and CASIA iris database show that not only the ‘small sample problem’ is overcome by KFDA, but also the correct recognition rate is higher than that of face recognition and iris recognition.
{"title":"Fusion and recognition of face and iris feature based on wavelet feature and KFDA","authors":"Junying Gan, Jun-Feng Liu","doi":"10.1109/ICWAPR.2009.5207475","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207475","url":null,"abstract":"In this paper, a novel approach to the fusion and recognition of face and iris image based on wavelet features and Kernel Fisher Discriminant Analysis (KFDA) is developed. Firstly, the dimension is reduced, the noise is eliminated, the storage space is saved and the efficiency is improved by Discrete Wavelet Transform (DWT) to face and iris image. Secondly, face and iris features are extracted and fusion by KFDA. Finally, Nearest Neighbor classifier is selected to perform recognition. Experimental results on ORL face database and CASIA iris database show that not only the ‘small sample problem’ is overcome by KFDA, but also the correct recognition rate is higher than that of face recognition and iris recognition.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126114490","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207494
Xiao-Wei Zhang, Linlin Zhao, Zhi-Juan Weng
In the digital watermarking technology based on wavelet transforms, it is of practical significance to improve the robustness of the JND (just noticeable difference) model and to control the probability of false alarm when extracting the watermarks from the watermarking systems. In the paper, a new watermark embedding algorithm has been studied and several experiments have been done as follows: a wavelet-based blind watermark detecting algorithm is proposed, which can determine the alarm threshold based on statistical characteristics, thereby quantitatively controlling the probability of false alarm; the JND model is improved, which enhances the robustness of JND model; and most of the embedded watermark can be effectively located even when the image is significantly modified. The algorithm proposed here is especially beneficial to blind extractions.
{"title":"A wavelet-based robust watermarking algorithm of high credibility","authors":"Xiao-Wei Zhang, Linlin Zhao, Zhi-Juan Weng","doi":"10.1109/ICWAPR.2009.5207494","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207494","url":null,"abstract":"In the digital watermarking technology based on wavelet transforms, it is of practical significance to improve the robustness of the JND (just noticeable difference) model and to control the probability of false alarm when extracting the watermarks from the watermarking systems. In the paper, a new watermark embedding algorithm has been studied and several experiments have been done as follows: a wavelet-based blind watermark detecting algorithm is proposed, which can determine the alarm threshold based on statistical characteristics, thereby quantitatively controlling the probability of false alarm; the JND model is improved, which enhances the robustness of JND model; and most of the embedded watermark can be effectively located even when the image is significantly modified. The algorithm proposed here is especially beneficial to blind extractions.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449900","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207439
Xu-Hong Yang, F. Huang, Gang Liu
The proposed approach is for the fusion of urban multi-spectral images. Three extracted texture features are merged by a synthesizing fusion rule. Experimental results indicate that the proposed method performs well in both spectral information and spatial information.
{"title":"Multi-spectral image fusion based on urban texture characteristics","authors":"Xu-Hong Yang, F. Huang, Gang Liu","doi":"10.1109/ICWAPR.2009.5207439","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207439","url":null,"abstract":"The proposed approach is for the fusion of urban multi-spectral images. Three extracted texture features are merged by a synthesizing fusion rule. Experimental results indicate that the proposed method performs well in both spectral information and spatial information.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124442851","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207449
Ming Shao, Yunhong Wang
Intrinsic images as a useful midlevel description attract more and more attentions in computer vision. According to Barrow and Tenenbaum's theory, a face image can be decomposed into two images: a reflectance image and an illumination image. Finding such decomposition remains difficult since it is an ill-posed problem. In this paper, we focus on a slightly easier problem: given a pair of multi-spectral facial images, can we recover its reflectance image and corresponding illumination image? Experiments show that it is promising and feasible. According to recent research in skin color model and Quotient Image, we propose a simple but effect method to derive the intrinsic image from a near infrared and a visual image. After modulating the grey distribution of visual images and dividing visual images by near infrared ones, we can recover its reflectance and illumination image. Experimental results show that our method is promising in image synthesis and processing.
{"title":"Extracting intrinsic images from multi-spectral","authors":"Ming Shao, Yunhong Wang","doi":"10.1109/ICWAPR.2009.5207449","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207449","url":null,"abstract":"Intrinsic images as a useful midlevel description attract more and more attentions in computer vision. According to Barrow and Tenenbaum's theory, a face image can be decomposed into two images: a reflectance image and an illumination image. Finding such decomposition remains difficult since it is an ill-posed problem. In this paper, we focus on a slightly easier problem: given a pair of multi-spectral facial images, can we recover its reflectance image and corresponding illumination image? Experiments show that it is promising and feasible. According to recent research in skin color model and Quotient Image, we propose a simple but effect method to derive the intrinsic image from a near infrared and a visual image. After modulating the grey distribution of visual images and dividing visual images by near infrared ones, we can recover its reflectance and illumination image. Experimental results show that our method is promising in image synthesis and processing.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132266704","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207431
Hui Liu, Wen-Sheng Chen
Linear Discriminant Analysis (LDA) is one of the commonly used statistical methods for feature extraction in face recognition tasks. However, LDA often suffers from the Small Sample Size (3S) problem, which occurs when the total number of training data is smaller than the dimension of input feature space. To deal with 3S problem, this paper proposes a novel approach for LDA-based face recognition using Random Projection (RP) technique. The advantages of random projection mainly include three aspects such as data-independent, dimensionality reduction and approximate distance preservation. So, based on the Johnson-Lindenstrauss theory, a new RP model is proposed for dimensionality reduction and simultaneously for learning the structure of the manifold with high accuracy. If the within-class scatter matrix is nonsingular in the randomly mapped feature space, LDA can be performed directly. Otherwise, RP will be followed by our previous Regularized Discriminant Analysis (RDA) approach for face recognition. Two public available databases, namely FERET and CMU PIE databases, are selected for evaluation. Comparing with PCA, DLDA and Fisherface approaches, our proposed method gives the best performance.
{"title":"A novel random projection model for Linear Discriminant Analysis based face recognition","authors":"Hui Liu, Wen-Sheng Chen","doi":"10.1109/ICWAPR.2009.5207431","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207431","url":null,"abstract":"Linear Discriminant Analysis (LDA) is one of the commonly used statistical methods for feature extraction in face recognition tasks. However, LDA often suffers from the Small Sample Size (3S) problem, which occurs when the total number of training data is smaller than the dimension of input feature space. To deal with 3S problem, this paper proposes a novel approach for LDA-based face recognition using Random Projection (RP) technique. The advantages of random projection mainly include three aspects such as data-independent, dimensionality reduction and approximate distance preservation. So, based on the Johnson-Lindenstrauss theory, a new RP model is proposed for dimensionality reduction and simultaneously for learning the structure of the manifold with high accuracy. If the within-class scatter matrix is nonsingular in the randomly mapped feature space, LDA can be performed directly. Otherwise, RP will be followed by our previous Regularized Discriminant Analysis (RDA) approach for face recognition. Two public available databases, namely FERET and CMU PIE databases, are selected for evaluation. Comparing with PCA, DLDA and Fisherface approaches, our proposed method gives the best performance.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132349810","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}
Shot segmentation is normally the groundwork for video retrieval, and which is one of the most important steps for content-based video retrieval. Although existing research on shot segmentation is more active, it still remains many challenges. In the paper, based on the principle of video compression, a novel shot segmentation algorithm called grid-mapping dynamic window (GMDW) is proposed by using changing windows, which is on the basis of DC coefficients in I-Frames. And the GMDW and the approach based on histogram of DC image are integrated into an operator called united difference degree in which it comes true that more accurate difference between two adjacent I-Frames is measured. Finally, more accurate shot boundaries or wrong shot boundaries are detected by the analysis of Macro-block in P or B frame between two adjacent I-Frames on a detected segment position. The experiments show that the Algorithm efficiently has improved the performance of shot detection, and to a certain extent, the complexity of the detection on gradual shot cuts is reduced.
{"title":"A novel shot segmentation algorithm based on grid-mapping dynamic windows in compressed videos","authors":"Ming-xin Zhang, Jinlong Zheng, Hua Li, Jin-yi Chang","doi":"10.1109/ICWAPR.2009.5207417","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207417","url":null,"abstract":"Shot segmentation is normally the groundwork for video retrieval, and which is one of the most important steps for content-based video retrieval. Although existing research on shot segmentation is more active, it still remains many challenges. In the paper, based on the principle of video compression, a novel shot segmentation algorithm called grid-mapping dynamic window (GMDW) is proposed by using changing windows, which is on the basis of DC coefficients in I-Frames. And the GMDW and the approach based on histogram of DC image are integrated into an operator called united difference degree in which it comes true that more accurate difference between two adjacent I-Frames is measured. Finally, more accurate shot boundaries or wrong shot boundaries are detected by the analysis of Macro-block in P or B frame between two adjacent I-Frames on a detected segment position. The experiments show that the Algorithm efficiently has improved the performance of shot detection, and to a certain extent, the complexity of the detection on gradual shot cuts is reduced.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127207074","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207465
Yang Jiao, Guanghai Li, Guangkai Sun, Ying-Kui Zhu, Yu-Bo Zhao
This paper discusses the leak location technology for buried gas pipeline. In the paper the leak model of buried gas pipeline is built, the leak location algorithm based correlation theory is designed, and the buried gas pipeline is tested in experiment site. Experimental results show that the method is effective on leak identification and leak location for the buried gas pipeline.
{"title":"Study on leak location technology for buried gas pipeline","authors":"Yang Jiao, Guanghai Li, Guangkai Sun, Ying-Kui Zhu, Yu-Bo Zhao","doi":"10.1109/ICWAPR.2009.5207465","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207465","url":null,"abstract":"This paper discusses the leak location technology for buried gas pipeline. In the paper the leak model of buried gas pipeline is built, the leak location algorithm based correlation theory is designed, and the buried gas pipeline is tested in experiment site. Experimental results show that the method is effective on leak identification and leak location for the buried gas pipeline.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131697802","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 : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207493
Wei Li, Tan Lin
Finding fixed points of nonexpansive mappings is a hot topic in different branches of mathematical and engineering sciences. In this paper, two iterative algorithms with errors are proposed and proved to be strongly convergent to fixed points of relatively of Lyapunov functional and generalized projection operator, etc. Moreover, it is demonstrated how to use the newly obtained iterative algorithms to approximate zero points of maximal monotone operators, which is also an important topic in the related areas.
{"title":"Iterative algorithm with errors for fixed points of relatively nonexpansive mappings","authors":"Wei Li, Tan Lin","doi":"10.1109/ICWAPR.2009.5207493","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207493","url":null,"abstract":"Finding fixed points of nonexpansive mappings is a hot topic in different branches of mathematical and engineering sciences. In this paper, two iterative algorithms with errors are proposed and proved to be strongly convergent to fixed points of relatively of Lyapunov functional and generalized projection operator, etc. Moreover, it is demonstrated how to use the newly obtained iterative algorithms to approximate zero points of maximal monotone operators, which is also an important topic in the related areas.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122557695","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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