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2009 Seventh International Conference on Advances in Pattern Recognition最新文献

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On-line Signature Verification: An Approach Based on Cluster Representations of Global Features 在线签名验证:基于全局特征聚类表示的方法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.30
D. S. Guru, H. Prakash, S. Manjunath
{"title":"On-line Signature Verification: An Approach Based on Cluster Representations of Global Features","authors":"D. S. Guru, H. Prakash, S. Manjunath","doi":"10.1109/ICAPR.2009.30","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.30","url":null,"abstract":"In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global features of signatures of each cluster are used to form an interval valued feature vector which is a symbolic representation for a cluster. Based on cluster representation, we propose methods of signature verification. We compare the feasibility of the proposed representation scheme for signature verification on a large MCYT_ signature database of 16500 signatures. Unlike other signature verification methods, the proposed method is simple and efficient and in addition, shows a remarkable reduction in EER.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115932361","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}
引用次数: 9
Performance Analysis for Image Super-Resolution Using Blur as a Cue 以模糊为线索的图像超分辨率性能分析
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.43
Deven Patel, S. Chaudhuri
{"title":"Performance Analysis for Image Super-Resolution Using Blur as a Cue","authors":"Deven Patel, S. Chaudhuri","doi":"10.1109/ICAPR.2009.43","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.43","url":null,"abstract":"A number of algorithms for image super-resolution  using multiple images, have been developed over the last two decades. On the other hand, a very less      amount of efforts  have been made to explore the issues regarding performance analysis of these methods. Since the  problem of super-resolution is often a   parameter estimation problem, the Cramer-Rao bound proves to be useful tool in analyzing the performance of the estimators.  We focus on the problem of      super-resolving with blur as a cue. In this paper  we look at the factors affecting the achievable bounds in super-resolution. We analyze the effects of the magnification factor, modeling noise and the spectrum of the signal to be super-resolved.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123391157","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}
引用次数: 1
Ringing Artifact Reduction in Blind Image Deblurring and Denoising Problems by Regularization Methods 基于正则化方法的盲图像去模糊降噪问题中的环形伪影降低
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.57
V. B. Surya Prasath, Arindama Singh
{"title":"Ringing Artifact Reduction in Blind Image Deblurring and Denoising Problems by Regularization Methods","authors":"V. B. Surya Prasath, Arindama Singh","doi":"10.1109/ICAPR.2009.57","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.57","url":null,"abstract":"Image deblurring and denoising are the main steps in early vision problems. A common problem in deblurring is the ringing artifacts created by trying to restore the unknown point spread function (PSF). The random noise present makes this task even harder. Variational blind deconvolution methods add a smoothness term for the PSF as well as for the unknown image. These methods can amplify the outliers correspond to noisy pixels. To remedy these problems we propose the addition of a first order reaction term which penalizes the deviation in gradients. This reduces the ringing artifact in blind image deconvolution. Numerical results show the effectiveness of this additional term in various blind and semi-blind image deblurring and denoising problems.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123539882","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}
引用次数: 13
A Hybrid Face Recognition Method Based on Structural and Holistic Features 基于结构特征和整体特征的混合人脸识别方法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.60
Suvendu Mandal, B. Dhara
{"title":"A Hybrid Face Recognition Method Based on Structural and Holistic Features","authors":"Suvendu Mandal, B. Dhara","doi":"10.1109/ICAPR.2009.60","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.60","url":null,"abstract":"In this paper we have proposed a novel face recognition method. This method is a hybrid of holistic and structural approaches. First, we locate the position of the nose tip and then we divide the image into eight octants with nose tip as the center. The petal projection method is employed on each octant to obtain a radial intensity profile. Then these radial intensity profiles are transformed by DCT for more compact and scale free representation. The transformed coefficient vectors are used to compute the similarity between the images. The proposed method is simple to implement and is efficient. The performance of the proposed method is evaluated on ORL database, and this offers a good trade-off between the recognition rate and the complexity of the method.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122972012","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}
引用次数: 13
A Novel Approach to Identification of Speakers from Their Hum 从说话人的嗡嗡声中识别说话人的新方法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.70
H. Patil, P. Jain, Robin Jain
{"title":"A Novel Approach to Identification of Speakers from Their Hum","authors":"H. Patil, P. Jain, Robin Jain","doi":"10.1109/ICAPR.2009.70","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.70","url":null,"abstract":"Automatic Speaker Recognition (ASR) deals with identification speakers with the help of machine from their voice. An ASR system will be efficient if the proper speaker-speci¿c features are extracted. Most of the state-of-the-art ASR systems use the natural speech signal (either read speech or spontaneous or contextual speech) from the subjects. In this paper, an attempt is made to identify speakers from their hum. The experiments are shown for Linear Prediction Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC), and Mel Frequency Cepstral Coefficients (MFCC) as input feature vectors to the polynomial classi¿er of 2nd and 3rd order approximation. Results are found to be better for MFCC than LP-based features.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114172415","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}
引用次数: 10
Analytic Phase-based Representation for Face Recognition 基于相位的人脸识别分析方法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.69
A. Sao, B. Yegnanarayana
{"title":"Analytic Phase-based Representation for Face Recognition","authors":"A. Sao, B. Yegnanarayana","doi":"10.1109/ICAPR.2009.69","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.69","url":null,"abstract":"A representation based on the  phase of analytic image is proposed to address  the issue of illumination variation in face recognition task. The problem of unwrapping in the computation of analytic phase is avoided by using trigonometric functions of phase. Template matching is used to compare the functions of analytic phase for face recognition. For template matching, the functions of the analytic phase are compressed using eigenanalysis. Performance of the face recognition is improved by using weights derived from the eigenvalues in the template matching.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132245554","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}
引用次数: 17
Proto-reduct Fusion Based Relevance Feedback in CBIR 基于原型约简融合的CBIR相关反馈
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.46
Samar Zutshi, Campbell Wilson, B. Srinivasan
{"title":"Proto-reduct Fusion Based Relevance Feedback in CBIR","authors":"Samar Zutshi, Campbell Wilson, B. Srinivasan","doi":"10.1109/ICAPR.2009.46","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.46","url":null,"abstract":"This paper proposes two related RF methods for use in CBIR. These two methods are based on a general classificatory analysis based framework for RF in CBMR that considers RF independently from retrieval. The proposed methods show how the user's information need expressed as a set of \"proto-reducts'' can be used as the basis of a re-weighting technique that can improve subsequent retrieval The performance of the proposed methods is studied on two image collections with different characteristics and compared against an existing RF method.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134398269","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}
引用次数: 8
Smoothening and Sharpening Effects of Theta in Complex Diffusion for Image Processing Theta在复杂扩散图像处理中的平滑和锐化效果
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.21
Jeny Rajan, K. Kannan, M. D. Kaimal
{"title":"Smoothening and Sharpening Effects of Theta in Complex Diffusion for Image Processing","authors":"Jeny Rajan, K. Kannan, M. D. Kaimal","doi":"10.1109/ICAPR.2009.21","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.21","url":null,"abstract":"In this paper we present a study on how the changing values of theta in complex diffusion affects the images. Normally it is considered that the low value of theta is suitable for image smoothening using complex diffusion, because at higher values of theta the imaginary part may feed back into the real part, creating wave-like ringing effects. Our study shows that as the value of theta increases, ringing effects starts appearing and reaches its peak at 1800 and then it starts disappearing, and the process continues in a 360 degree cycle, where the peak of the wave indicates image with maximum ringing effects (or the maximum sharpened image, property of inverse diffusion). Regarding non-linear complex diffusion we experimentally proved the smoothening is fast at higher values of theta, which can be used for image denoising purpose.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116281865","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}
引用次数: 7
Model Based Clustering of Audio Clips Using Gaussian Mixture Models 基于高斯混合模型的音频片段聚类
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.92
S. Chandrakala, C. Sekhar
{"title":"Model Based Clustering of Audio Clips Using Gaussian Mixture Models","authors":"S. Chandrakala, C. Sekhar","doi":"10.1109/ICAPR.2009.92","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.92","url":null,"abstract":"The task of clustering multi-variate trajectory data of varying length exists in various domains. Model-based methods are capable of handling varying length trajectories without changing the length or structure. Hidden Markov models (HMMs) are widely used for trajectory data modeling. However, HMMs are not suitable for trajectories of long duration. In this paper, we propose a similarity based representation for multi-variate, varying length trajectories of long duration using Gaussian mixture models. Each trajectory is modeled by a Gaussian mixture model (GMM). The log-likelihood of a trajectory for a given GMM model is used as a similarity score. The scores corresponding to all the trajectories in the given data set and all the GMMs are used to form a score matrix that is used in a clustering algorithm. The proposed model based clustering method is applied on the audio clips which are multi-variate trajectories of varying length and long duration. The performance of the proposed method is much better than the method that uses a fixed length representation for an audio clip based on the perceptual features.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123084997","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}
引用次数: 3
Facial Expression Recognition with Multi-channel Deconvolution 基于多通道反卷积的面部表情识别
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.95
G. Krell, R. Niese, B. Michaelis
{"title":"Facial Expression Recognition with Multi-channel Deconvolution","authors":"G. Krell, R. Niese, B. Michaelis","doi":"10.1109/ICAPR.2009.95","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.95","url":null,"abstract":"Facial expression recognition is an important task in human computer interaction systems to include emotion processing.  In this work we present a Multi-Channel Deconvolution method for post processing of face expression data derived from video sequences. Photogrammetric techniques are applied to deter¬mine real world geometric measures and to build the feature vector. SVM classification is used to classify a limited number of emotions from the feature vector. A Multi-Channel Deconvolution removes ambiguities at the transitions between different classified emotions. This way, typical temporal behavior of facial expression change is considered.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122023319","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}
引用次数: 2
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