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

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Traffic Sign Detection and Pattern Recognition Using Support Vector Machine 基于支持向量机的交通标志检测与模式识别
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.58
Kiran C.G., L. V. Prabhu, A. V, R. K
{"title":"Traffic Sign Detection and Pattern Recognition Using Support Vector Machine","authors":"Kiran C.G., L. V. Prabhu, A. V, R. K","doi":"10.1109/ICAPR.2009.58","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.58","url":null,"abstract":"A vision based vehicle guidance system must be able to detect and recognize traffic signs. Traffic sign recognition systems collect information about road signs and helps the driver to make timely decisions, making driving safer and easier. This paper deals with the detection and recognition of traffic signs from image sequences using the colour information. Colour based segmentation techniques are employed for traffic sign detection. In order to improve the performance of segmentation, we used the product of enhanced hue and saturation components. To obtain better shape classification performance, we used linear support vector machine with the Distance to Border features of the segmented blobs. Recognition of traffic signs are implemented using multi-classifier non-linear support vector machine with edge related pixels of interest as the feature.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"151 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":"116522323","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: 79
Qualitative Weight Assignment for Multimodal Biometric Fusion 多模态生物特征融合的定性权重分配
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.23
Ramachandra Raghavendra, G. Kumar, A. Rao
{"title":"Qualitative Weight Assignment for Multimodal Biometric Fusion","authors":"Ramachandra Raghavendra, G. Kumar, A. Rao","doi":"10.1109/ICAPR.2009.23","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.23","url":null,"abstract":"Multimodal biometrics has drawn lot of attention in recent days as it provides more reliable scheme for person verification. Multimodal biometrics includes the fusion of information from different modalities. This paper presents a novel method for assigning weights before performing fusion at match score level. The proposed method is based on False Acceptance Rate (FAR) and Genuine Acceptance Rate (GAR) obtained for each modality and weights are assigned on match scores of individual modality before performing match score level fusion. Extensive experiments carried out on three different build multimodal biometric databases shows the efficacy of the proposed method","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"34 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":"114842696","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: 25
Upper and Lower Grey-Level Adaptive Morphological Operators 上下灰度自适应形态学算子
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.79
Corinne Vachier
{"title":"Upper and Lower Grey-Level Adaptive Morphological Operators","authors":"Corinne Vachier","doi":"10.1109/ICAPR.2009.79","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.79","url":null,"abstract":"Morphological operators designed for grey-scale functions process every points of the space identically whatever their luminance. In many situations however, it is interesting to modulate the amount of processing according to the local grey-level. This leads to the idea of intensity-adaptive morphological operators. A simple way to construct such operators is to threshold the function at every grey-value, then to apply set operators to the level sets obtained in this way, and finally to reconstruct a new transformed function from the transformed level sets. The reconstruction's step is not straightforward since the transformed level sets are not obligatorily nested. Two schemes of stacking reinvestigated in the present paper that lead to two kinds of intensity-adaptive operators: the upper and  lower adaptive operators. Those operators are complementary in the sense that, by coupling, one defines adjunctions and consequently, by composition, one defines intensity-adaptive morphological openings and closings. The theoretical study of grey-level adaptive morphological operators is supplemented of some examples that illustrate the potential of the investigated operators in image filtering applications.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"90 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":"132628356","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: 5
A Quality Based Motion Estimation Criterion for Temporal Coding of Video 基于质量的视频时间编码运动估计准则
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.66
R. Purwar, N. Prakash, N. Rajpal
{"title":"A Quality Based Motion Estimation Criterion for Temporal Coding of Video","authors":"R. Purwar, N. Prakash, N. Rajpal","doi":"10.1109/ICAPR.2009.66","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.66","url":null,"abstract":"In video compression, motion compensation techniques are used for removal of temporal redundancy and it is the block based matching concept which is most popular among them. In such matching techniques, Mean Absolute Difference (MAD) is widely accepted as the matching criterion because of its simplicity and low computation. Since MAD considers only average error value in a block for matching purposes while ignoring individual difference between the pixels, the matching may not be more accurate. In this paper, a new block matching criterion is being suggested and is experimentally compared with two other matching criterions including MAD, using four parameters and the results are better for the proposed one.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"61 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":"126376321","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: 6
Image Denoising Using Edge Model-based Representation of Laplacian Subbands 基于拉普拉斯子带表示的边缘模型图像去噪
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.29
M. Nema, S. Rakshit, S. Chaudhuri
{"title":"Image Denoising Using Edge Model-based Representation of Laplacian Subbands","authors":"M. Nema, S. Rakshit, S. Chaudhuri","doi":"10.1109/ICAPR.2009.29","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.29","url":null,"abstract":"This paper presents a novel method of removing unstructured, spurious artifacts (more popularly called noise) from images. This method uses an edge model-based representation of Laplacian subbands and deals with noise at Laplacian subband levels to reduce it effectively. As the prominent edges are retained in their original form in the denoised images, the proposed method can be classified as an edge preserving denoising scheme. Laplacian subbands are represented using a Primitive Set (PS) consisting of 7 x 7 subimages of sharp and blurred Laplacian edge elements. The choice of edge model-based representation provides greater flexibility in removing characteristic artifacts from noise sources.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"44 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":"127310838","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: 11
Online Character Recognition Using Elastic Curvature Matching 基于弹性曲率匹配的在线字符识别
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.94
Jong-Hoon Ahn, Jihyun Lee, Jinsu Jo, Y. Choi, Yillbyung Lee
{"title":"Online Character Recognition Using Elastic Curvature Matching","authors":"Jong-Hoon Ahn, Jihyun Lee, Jinsu Jo, Y. Choi, Yillbyung Lee","doi":"10.1109/ICAPR.2009.94","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.94","url":null,"abstract":"An efficient method for online character recognition is suggested. It consists of two steps: curvature extraction and curvature matching. The online signal with a single stroke is a sequence of two-dimensional positional vectors whereas its curvature is one-dimensional. Elastic curvature matching is basically a 1D-to-1D matching problem between curvatures of reference and test characters, and one-dimensionality of curvature makes the matching problem more quick and easy than 2D-to-2D matching. We show the results obtained from applying it to online digit recognition and discuss them.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"203 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":"131647206","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: 6
Using Modified Contour Features and SVM Based Classifier for the Recognition of Persian/Arabic Handwritten Numerals 基于改进轮廓特征和SVM分类器的波斯语/阿拉伯语手写数字识别
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.14
Alireza Alaei, U. Pal, P. Nagabhushan
{"title":"Using Modified Contour Features and SVM Based Classifier for the Recognition of Persian/Arabic Handwritten Numerals","authors":"Alireza Alaei, U. Pal, P. Nagabhushan","doi":"10.1109/ICAPR.2009.14","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.14","url":null,"abstract":"In this paper, we propose a robust and efficient feature set based on modified contour chain code to achieve higher recognition accuracy of Persian/Arabic numerals. In classification part, we employ support vector machine (SVM) as classifier. Feature set consists of 196 dimensions, which are the chain-code direction frequencies in the contour pixels of input image. We evaluated our scheme on 80,000 handwritten samples of Persian numerals. Using 60,000 samples for training, we tested our scheme on other 20,000 samples and obtained 98.71% correct recognition rate. Further, we obtained 99.37% accuracy using five-fold cross validation technique on 80,000 dataset.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"1 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":"114187433","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: 51
Belief Function Theory Based Biometric Match Score Fusion: Case Studies in Multi-instance and Multi-unit Iris Verification 基于信念函数理论的生物特征匹配分数融合:多实例和多单元虹膜验证案例研究
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.98
Mayank Vatsa, Richa Singh, A. Noore, S. Singh
{"title":"Belief Function Theory Based Biometric Match Score Fusion: Case Studies in Multi-instance and Multi-unit Iris Verification","authors":"Mayank Vatsa, Richa Singh, A. Noore, S. Singh","doi":"10.1109/ICAPR.2009.98","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.98","url":null,"abstract":"This paper presents a framework for multi-biometric match score fusion when non-ideal conditions cause conflict in the results of different classifiers. The proposed framework uses belief function theory to effectively fuse the match scores and density estimation technique to compute the belief assignments. Fusion is performed using belief models such as Transferable Belief Model (TBM) and Proportional Conflict Redistribution (PCR) Rule followed by the likelihood ratio based decision making. Experimental results on multi-instance and multi-unit iris verification show that the proposed fusion framework with PCR rule yields the best verification accuracy even when individual biometric classifiers provide highly conflicting match scores.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"12 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":"114594089","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: 11
Eigen-domain Relighting of Face Images for Illumination-invariant Face Verification 光照不变人脸验证中人脸图像的特征域重光照
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.62
V. Pathangay, Sukhendu Das
{"title":"Eigen-domain Relighting of Face Images for Illumination-invariant Face Verification","authors":"V. Pathangay, Sukhendu Das","doi":"10.1109/ICAPR.2009.62","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.62","url":null,"abstract":"In this paper, we propose a method to exploit the uniqueness in the illumination variations on the face image of a subject for face verification. Using the 3D wireframe model of a face, illumination variations are synthetically generated by rendering it with texture to produce virtual face images. When these virtual and a set of real face images are transformed in eigenspace, they form two separate clusters for the virtual and real-world faces. In addition, the cluster corresponding to set of virtual faces for any subject is more compact compared to real face image cluster. Therefore, we take the virtual face cluster as the reference and find a transformation that takes real face features closer to the reference virtual face cluster. In this paper, we propose subject-specific relighting transformations that relight the real face feature in eigenspace into a more compact virtual face feature cluster. This transformation is computed and stored during training. During testing, subject-specific transformations are applied on the eigen-feature of the realface image before computing the distance from the reference cluster of the claimed subject. We report verification results on frontal face images with various lighting directions of all 68 subjects of the PIE database, and show using receiver operating characteristic (ROC) curves and equal error rates(EER) that the proposed subject-specific eigen-relighting gives significantly better face verification performance when compared with a baseline system without eigen-relighting.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"35 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":"122307881","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: 0
Classification by Linearity Assumption 线性假设分类
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.11
A. Majumdar, A. Bhattacharya
{"title":"Classification by Linearity Assumption","authors":"A. Majumdar, A. Bhattacharya","doi":"10.1109/ICAPR.2009.11","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.11","url":null,"abstract":"Recently a classifier was proposed that was based on the assumption: the training samples for a particular class form a linear basis for any new test sample. This assumption is a generalization of the Nearest Neighbour classifier. In the previous work, the classifier was built upon this assumption required solving a complex optimisation problem. The optimisation method was time consuming and restrictive in application. In this work our proposed algorithm takes care of the previous problems keeping the basic assumption intact. We also offer generalisations of the basic assumption. Comparative experimental results on some UCI machine learning databases show that our proposed generalised classifier is performs as good as other well known techniques like Nearest Neighbour and Support Vector Machine.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"1 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":"115930441","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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