Pub Date : 2009-07-12DOI: 10.1109/ICWAPR.2009.5207487
Zhi Shi, Hai-Yan Xing, B. Peng
In this paper, Fourier analysis are first presented in the two-dimensional context. Then existing work on the representation of wavelets on ZN is extented to two dimensions. A necessary and sufficient condition on the existence of biorthonormal wavelets on ZN1 × ZN2 is derived. A method for constructing biorthonormal wavelest on ZN1 × ZN2 is presented and their properties is investigated by mean of time-frequency analysis method, matrix theory and operator theory.
{"title":"Two-dimensional biorthonormal wavelet on ZN1 × ZN2","authors":"Zhi Shi, Hai-Yan Xing, B. Peng","doi":"10.1109/ICWAPR.2009.5207487","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207487","url":null,"abstract":"In this paper, Fourier analysis are first presented in the two-dimensional context. Then existing work on the representation of wavelets on Z<inf>N</inf> is extented to two dimensions. A necessary and sufficient condition on the existence of biorthonormal wavelets on Z<inf>N1</inf> × Z<inf>N2</inf> is derived. A method for constructing biorthonormal wavelest on Z<inf>N1</inf> × Z<inf>N2</inf> is presented and their properties is investigated by mean of time-frequency analysis method, matrix theory and operator theory.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"8 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":"115278947","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.2009.5207472
Xue Zhang, S. Zhong
As the steganography technology becomes diversified recently, a good blind steganalyzer is in great request. In recent works, a blind steganalysis based on statistical moments of wavelet characteristic functions (MWCF) is proposed, but it has poor generalization ability to some extent. To improve this weakness, the F-score feature selection method is used to filter irrelevant, redundant features calculated from MWCF. By combining MWCF and F-score method, an improved blind steganalysis method is proposed in this article, called FS-MWCF method in short. Experimental results show that the FS-MWCF method has better generalization ability and lower classifying time complexity, less than half of that using MWCF method.
{"title":"Blind steganalysis method for BMP images based on statistical MWCF and F-score method","authors":"Xue Zhang, S. Zhong","doi":"10.1109/ICWAPR.2009.5207472","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207472","url":null,"abstract":"As the steganography technology becomes diversified recently, a good blind steganalyzer is in great request. In recent works, a blind steganalysis based on statistical moments of wavelet characteristic functions (MWCF) is proposed, but it has poor generalization ability to some extent. To improve this weakness, the F-score feature selection method is used to filter irrelevant, redundant features calculated from MWCF. By combining MWCF and F-score method, an improved blind steganalysis method is proposed in this article, called FS-MWCF method in short. Experimental results show that the FS-MWCF method has better generalization ability and lower classifying time complexity, less than half of that using MWCF method.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"148 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":"132652027","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.2009.5207495
Gang Wang, Baoqin Wang, Y. Fu
Generalized continuous frames are natural generalization of continuous and discrete frames in Hilbert space which include many recent generalization of frames. In this paper, we study the stability of generalized continuous frames, several meaningful results are obtained.
{"title":"A study on the stability of g-continuous frames","authors":"Gang Wang, Baoqin Wang, Y. Fu","doi":"10.1109/ICWAPR.2009.5207495","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207495","url":null,"abstract":"Generalized continuous frames are natural generalization of continuous and discrete frames in Hilbert space which include many recent generalization of frames. In this paper, we study the stability of generalized continuous frames, several meaningful results are obtained.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"1 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":"128435503","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.2009.5207423
Zhi Shi, Julian Han
In this paper, an operational matrix of integration based on Haar wavelets is introduced, and a procedure for applying the matrix to solve biharmonic equations is formulated. The technique can be used for solving boundary value problems of one-dimensional biharmonic equations. The efficiency of the proposed method is tested with the aid of an example.
{"title":"Numerical solution of one-dimensional biharmonic equations using Haar wavelets","authors":"Zhi Shi, Julian Han","doi":"10.1109/ICWAPR.2009.5207423","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207423","url":null,"abstract":"In this paper, an operational matrix of integration based on Haar wavelets is introduced, and a procedure for applying the matrix to solve biharmonic equations is formulated. The technique can be used for solving boundary value problems of one-dimensional biharmonic equations. The efficiency of the proposed method is tested with the aid of an example.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"1 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":"130611774","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.2009.5207426
Bing Luo, Junying Gan
In PCB SMT assembly products automated machine vision inspection, images registration is necessary for getting an entire PCB image. Because of inhomogeneous illumination in engineering images capturing, conventional mosaic method can not deal with it. High frequency coefficients of wavelet decomposition reflect the contour of the image and that of illumination variety is relative small. So images registration based on wavelet decomposition can be robust for machine vision inspection. Using projection of wavelet decomposition coefficients to instead of mutual correlation can simplify the calculation from 2D to 1D. Experimental results show this approach is effective, robust and quick.
{"title":"Inhomogeneous illuminated images registration based on wavelet decomposition","authors":"Bing Luo, Junying Gan","doi":"10.1109/ICWAPR.2009.5207426","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207426","url":null,"abstract":"In PCB SMT assembly products automated machine vision inspection, images registration is necessary for getting an entire PCB image. Because of inhomogeneous illumination in engineering images capturing, conventional mosaic method can not deal with it. High frequency coefficients of wavelet decomposition reflect the contour of the image and that of illumination variety is relative small. So images registration based on wavelet decomposition can be robust for machine vision inspection. Using projection of wavelet decomposition coefficients to instead of mutual correlation can simplify the calculation from 2D to 1D. Experimental results show this approach is effective, robust and quick.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"4 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":"123993630","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.2009.5207466
Yintang Dai, Shihan Zhang
This paper presents a fast labeled graph matching algorithm called Graph Explorer (GE) algorithm, which can be categorized into the tree search based graph matching (TSGM) algorithms of exact graph/subgraph matching. Not like the other node-centric TSGM algorithms, the GE algorithm focuses on edges matching. It constructs search state of partially matched subgraph by edge and edge. It converts graph matching problem into a path search problem in the space of search states. Under the guidance of the search path, it avoided repeated label checking by inheriting state tree structure for caching and fast visiting matched nodes and edge. By a carefully optimized search route and intelligent backtracking, GE algorithm avoided a large amount of the invalid search states and improved performance to be almost linear to the number of edges of pattern graph with low ambiguity. While traditional TSGM are suffering the call stack overflow problem caused by recursive function calls, it overcame this problem by a dynamic state queue. It can handle extra large size of pattern (up to 10,000 nodes). The experiment shows the performance of GE is better than similar algorithms and it is more resistant to ambiguities.
{"title":"A fast labeled graph matching algorithm based on edge matching and guided by search route","authors":"Yintang Dai, Shihan Zhang","doi":"10.1109/ICWAPR.2009.5207466","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207466","url":null,"abstract":"This paper presents a fast labeled graph matching algorithm called Graph Explorer (GE) algorithm, which can be categorized into the tree search based graph matching (TSGM) algorithms of exact graph/subgraph matching. Not like the other node-centric TSGM algorithms, the GE algorithm focuses on edges matching. It constructs search state of partially matched subgraph by edge and edge. It converts graph matching problem into a path search problem in the space of search states. Under the guidance of the search path, it avoided repeated label checking by inheriting state tree structure for caching and fast visiting matched nodes and edge. By a carefully optimized search route and intelligent backtracking, GE algorithm avoided a large amount of the invalid search states and improved performance to be almost linear to the number of edges of pattern graph with low ambiguity. While traditional TSGM are suffering the call stack overflow problem caused by recursive function calls, it overcame this problem by a dynamic state queue. It can handle extra large size of pattern (up to 10,000 nodes). The experiment shows the performance of GE is better than similar algorithms and it is more resistant to ambiguities.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"21 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":"128590610","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.2009.5207425
F. Chou, Jie-Cyun Huang
In this paper, a pipelining empirical mode decomposition is presented to reduce the computing time of the emotionalized spontaneous speaker or speech recognition processing. This is a novel approach for integrating the pipelining technique into the standard empirical mode decomposition of the Hilbert-Huang transform. In addition, there is reduced about 45% of the computing time when the emotionalized spoken signal through our segmentation and pipelining processes. Based on the designed processing of emotionalized spontaneous speaker or speech recognition, the segmented and processed voice signals are recomposed back for constructing the speech and speaker models, or to identify which existed model is the most similar one. In the final part of this paper, a comparison of the speech recognized rate between standard and pipelining empirical mode decompositions are presented, and an equivalent effect in the recognition will be found. In practice, speaker or speech recognitions in an emotionalized spontaneous speech are very difficult. The existing speech recognition methods often fail to capture inherent voiceprint features from an emotionalized speech, such as the voice with a passionate intonation. And some of the existed methods to extract the pure voiceprint from an emotionalized spoken signal are very expensive in computation and time, so that technique is impossible to use in a real-time environment like smart houses. But, this paper presents a solution to improve the emotionalized spontaneous speaker or speech recognition processing to fit the real-time request.
{"title":"Apply pipelining empirical mode decomposition to accelerate an emotionalized speech processing","authors":"F. Chou, Jie-Cyun Huang","doi":"10.1109/ICWAPR.2009.5207425","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207425","url":null,"abstract":"In this paper, a pipelining empirical mode decomposition is presented to reduce the computing time of the emotionalized spontaneous speaker or speech recognition processing. This is a novel approach for integrating the pipelining technique into the standard empirical mode decomposition of the Hilbert-Huang transform. In addition, there is reduced about 45% of the computing time when the emotionalized spoken signal through our segmentation and pipelining processes. Based on the designed processing of emotionalized spontaneous speaker or speech recognition, the segmented and processed voice signals are recomposed back for constructing the speech and speaker models, or to identify which existed model is the most similar one. In the final part of this paper, a comparison of the speech recognized rate between standard and pipelining empirical mode decompositions are presented, and an equivalent effect in the recognition will be found. In practice, speaker or speech recognitions in an emotionalized spontaneous speech are very difficult. The existing speech recognition methods often fail to capture inherent voiceprint features from an emotionalized speech, such as the voice with a passionate intonation. And some of the existed methods to extract the pure voiceprint from an emotionalized spoken signal are very expensive in computation and time, so that technique is impossible to use in a real-time environment like smart houses. But, this paper presents a solution to improve the emotionalized spontaneous speaker or speech recognition processing to fit the real-time request.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"23 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":"121754659","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.2009.5207473
W. Lu, Yan Bai, Yi Tang, Yanfang Tao
We focus on a semi-supervised framework that incorporates labeled and unlabeled data in a general- purpose learner. We proposed a semi-learning algorithm based on a novel form of regularization that allows us to emphasize the complexity of the representation of learners. With operator method, the optimal learner learned by such algorith is explicitly represented by sampling operator when the hyperspace is a reproducing kernel Hilbert space. Based on such explicit representation, a simple and convenient algorithm is designed. Some preliminary experiments validate the effectiveness of the algorith.
{"title":"An operator method for semi-supervised learning","authors":"W. Lu, Yan Bai, Yi Tang, Yanfang Tao","doi":"10.1109/ICWAPR.2009.5207473","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207473","url":null,"abstract":"We focus on a semi-supervised framework that incorporates labeled and unlabeled data in a general- purpose learner. We proposed a semi-learning algorithm based on a novel form of regularization that allows us to emphasize the complexity of the representation of learners. With operator method, the optimal learner learned by such algorith is explicitly represented by sampling operator when the hyperspace is a reproducing kernel Hilbert space. Based on such explicit representation, a simple and convenient algorithm is designed. Some preliminary experiments validate the effectiveness of the algorith.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"85 22 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":"126532126","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.2009.5207415
Hanxin Chen, M. Zuo
In this paper, we propose a novel method for identification of gear crack from the low-frequency modulated vibration signal, based on Hilbert transform and adaptive wavelet transform (AWT). Hilbert transform is used to present the envelope of the modulated vibration signal to show the modulating frequency. AWT is applied to process the modulated vibration signal by Hilbert transform. The proposed AWT can match the vibration signal with the meshing frequency and its harmonics, the coupling frequency, the carrier frequency, and their sidebands by an optimized wavelet. The model-based method by AWT is applied to extract the envelop features from the modulated vibration signal. Both simulated and experimental vibration signals are used to test the proposed method.
{"title":"Fault detection of gearbox with vibration signal analysis by a linear combination of adaptive wavelets","authors":"Hanxin Chen, M. Zuo","doi":"10.1109/ICWAPR.2009.5207415","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207415","url":null,"abstract":"In this paper, we propose a novel method for identification of gear crack from the low-frequency modulated vibration signal, based on Hilbert transform and adaptive wavelet transform (AWT). Hilbert transform is used to present the envelope of the modulated vibration signal to show the modulating frequency. AWT is applied to process the modulated vibration signal by Hilbert transform. The proposed AWT can match the vibration signal with the meshing frequency and its harmonics, the coupling frequency, the carrier frequency, and their sidebands by an optimized wavelet. The model-based method by AWT is applied to extract the envelop features from the modulated vibration signal. Both simulated and experimental vibration signals are used to test the proposed method.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"345 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":"133600592","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.2009.5207498
Hong-Jiao Ma, Yonghui Hu, Jian-Feng Wu, Jigang Wang, W. Guo
In connection with difficultly establishing accurate mathematical model by extended Kalman filter in data process in GPS/INS Integrated Navigation, lifting wavelet algorithm using Translation-invariant method is applied to reduce noise of observational signal. Pseudo-Gibbs appearances of signal that are produced in discontinuity points can effectively be eliminated by Translation-invariant. Lifting wavelet algorithm is more accurate and quicker than traditional Mallat wavelet method. Compared with traditional soft and hard threshold functions, improved threshold function is more continuous in navigation signal process. Study shows improved Wavelet De-noising Method is a superior method in saving calculation time and improving Navigation performance.
{"title":"Application of lifting scheme Translation-invariant Wavelet De-noising Method in GPS/INS Integrated Navigation","authors":"Hong-Jiao Ma, Yonghui Hu, Jian-Feng Wu, Jigang Wang, W. Guo","doi":"10.1109/ICWAPR.2009.5207498","DOIUrl":"https://doi.org/10.1109/ICWAPR.2009.5207498","url":null,"abstract":"In connection with difficultly establishing accurate mathematical model by extended Kalman filter in data process in GPS/INS Integrated Navigation, lifting wavelet algorithm using Translation-invariant method is applied to reduce noise of observational signal. Pseudo-Gibbs appearances of signal that are produced in discontinuity points can effectively be eliminated by Translation-invariant. Lifting wavelet algorithm is more accurate and quicker than traditional Mallat wavelet method. Compared with traditional soft and hard threshold functions, improved threshold function is more continuous in navigation signal process. Study shows improved Wavelet De-noising Method is a superior method in saving calculation time and improving Navigation performance.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"162 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":"131653047","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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