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Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.最新文献

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A learning model for multiple-prototype classification of strings 字符串多原型分类的学习模型
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.49
R. Cárdenas
{"title":"A learning model for multiple-prototype classification of strings","authors":"R. Cárdenas","doi":"10.1109/ICPR.2004.49","DOIUrl":"https://doi.org/10.1109/ICPR.2004.49","url":null,"abstract":"An iterative learning method to update labeled string prototypes for a 1-nearest prototype (1-np) classification is introduced. Given a (typically reduced) set of initial string prototypes and a training set, it iteratively updates prototypes to better discriminate training samples. The update rule, which is based on the edit distance, adjusts a prototype by removing those local differences which are both frequent with respect to same-class closer training strings and infrequent with respect to different-class closer training strings. Closer training strings are defined by unsupervised clustering. The process continues until prototypes converge. Its main innovation is to provide a non-random local update rule to \"move\" a string prototype towards a number of string samples. A series of learning/classification experiments show a better 1-np performance of the updated prototypes with respect to the initial ones, that were originally selected to guarantee a good classification.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121934057","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: 4
The pattern classification based on the nearest feature midpoints 基于最接近的特征中点的模式分类
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334562
Zonglin Zhou, C. Kwoh
{"title":"The pattern classification based on the nearest feature midpoints","authors":"Zonglin Zhou, C. Kwoh","doi":"10.1109/ICPR.2004.1334562","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334562","url":null,"abstract":"In this paper, we propose a novel method, called the nearest feature midpoint (NFM), for pattern classification. Any two feature points of the same class are generalized by the feature midpoint (FM) between them. The representational capacity of available prototypes is thus expanded. The classification is based on the nearest distance from the query feature point to each FM. A theoretical proof is provided in this paper to show that for the n-dimensional Gaussian distribution, the classification based on the NFM distance metric achieves the least error probability as compared to those based on any other points on the feature lines. Furthermore, a theoretical investigation indicates that under some assumption the NFL is approximately equivalent to the NFM when the dimension of the feature space is high. The empirical evaluation on a simulated data set concurs with all the theoretical investigations.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127972281","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: 14
An intelligent real-time vision system for surface defect detection 一种用于表面缺陷检测的智能实时视觉系统
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334512
H. Jia, Y. Murphey, Jianjun Shi, Tzyy-Shuh Chang
{"title":"An intelligent real-time vision system for surface defect detection","authors":"H. Jia, Y. Murphey, Jianjun Shi, Tzyy-Shuh Chang","doi":"10.1109/ICPR.2004.1334512","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334512","url":null,"abstract":"In recent years, there is an increased need for quality control in the manufacturing sectors. In the steel making, the rolling operation is often the last process that significantly affects the bulk microstructure of the steel. The cost of having defects on rolled steel is high because it takes more than 5000 KW-Hr to produce a ton of steel. Early detection of defects can reduce product damage and manufacturing cost. This paper describes a real-time visual inspection system that uses support vector machine to automatically learn complicated defect patterns. Based on the experimental results generated from over one thousand images, the proposed system is found to be effective in detecting steel surface detects. The speed of the system for feature extraction and defect detection is less than 6 msec per one-megabyte image.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127990028","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: 169
Conformal method for quantitative shape extraction: Performance evaluation 定量形状提取的保形法:性能评价
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1333698
G. Kamberov, G. Kamberova
{"title":"Conformal method for quantitative shape extraction: Performance evaluation","authors":"G. Kamberov, G. Kamberova","doi":"10.1109/ICPR.2004.1333698","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1333698","url":null,"abstract":"We evaluate our developed conformal method for quantitative shape extraction from unorganized 3D oriented point clouds. The conformal method has been tested previously on real, noisy, 3D data. Here we focus on the empirical evaluation of its performance on synthetic, ground truth data, and comparisons with other methods for quantitative extraction of mean and Gauss curvatures presented in the literature.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121700895","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
Head pose estimation by nonlinear manifold learning 基于非线性流形学习的头部姿态估计
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1333802
B. Raytchev, Ikushi Yoda, K. Sakaue
{"title":"Head pose estimation by nonlinear manifold learning","authors":"B. Raytchev, Ikushi Yoda, K. Sakaue","doi":"10.1109/ICPR.2004.1333802","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1333802","url":null,"abstract":"In This work we propose an isomap-based nonlinear alternative to the linear subspace method for manifold representation of view-varying faces. Being interested in user-independent head pose estimation, we extend the isomap model (J.B. Tenenbaum et al., 2000) to be able to map (high-dimensional) input data points which are not in the training data set into the dimensionality-reduced space found by the model. From this representation, a pose parameter map relating the input face samples to view angles is learnt. The proposed method is evaluated on a large database of multi-view face images in comparison to two other recently proposed subspace methods.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"355 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115932273","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: 178
Galilean-diagonalized spatio-temporal interest operators 伽利略对角化时空兴趣算子
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.407
T. Lindeberg, A. Akbarzadeh, I. Laptev
{"title":"Galilean-diagonalized spatio-temporal interest operators","authors":"T. Lindeberg, A. Akbarzadeh, I. Laptev","doi":"10.1109/ICPR.2004.407","DOIUrl":"https://doi.org/10.1109/ICPR.2004.407","url":null,"abstract":"This paper presents a set of image operators for detecting regions in space-time where interesting events occur. To define such regions of interest, we compute a spatio-temporal second-moment matrix from a spatio-temporal scale-space representation, and diagonalize this matrix locally, using a local Galilean transformation in space-time, optionally combined with a spatial rotation, so as to make the Galilean invariant degrees of freedom explicit. From the Galilean-diagonalized descriptor so obtained, we then formulate different types of space-time interest operators, and illustrate their properties on different types of image sequences.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131998831","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: 14
Dense stereo matching using kernel maximum likelihood estimation 使用核最大似然估计的密集立体匹配
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334461
A. Jagmohan, Maneesh Kumar Singh, N. Ahuja
{"title":"Dense stereo matching using kernel maximum likelihood estimation","authors":"A. Jagmohan, Maneesh Kumar Singh, N. Ahuja","doi":"10.1109/ICPR.2004.1334461","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334461","url":null,"abstract":"There has been much interest, recently, in the use of Bayesian formulations for solving image correspondence problems. For the two-view stereo matching problem, typical Bayesian formulations model the disparity prior as a pairwise Markov random field (MRF). Approximate inference algorithms for MRFs, such as graph cuts or belief propagation, treat the stereo matching problem as a labelling problem yielding discrete valued disparity estimates. In this paper, we propose a novel robust Bayesian formulation based on the recently proposed kernel maximum likelihood (KML) estimation framework. The proposed formulation uses probability density kernels to infer the posterior probability distribution of the disparity values. We present an efficient iterative algorithm, which uses a variational approach to form a KML estimate from the inferred distribution. The proposed algorithm yields continuous-valued disparity estimates, and is provably convergent. The proposed approach is validated on standard stereo pairs, with known sub-pixel disparity ground-truth data.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"172 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132030450","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
Watershed lines suppression by waterfall marker improvement and line-neighbourhood analysis 瀑布标记改进和线邻域分析抑制流域线
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334215
F. Soares, F. Muge
{"title":"Watershed lines suppression by waterfall marker improvement and line-neighbourhood analysis","authors":"F. Soares, F. Muge","doi":"10.1109/ICPR.2004.1334215","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334215","url":null,"abstract":"In this paper, we present a new self-sufficient image segmentation method based on watershed-lines neighbourhood. This work-study uses two morphological concepts, watershed and waterfall, for the development of a line-based catalogue concerning neighbourhood analysis. Innovation in waterfall hierarchical evolution is achieved with a marker-constraint implementation along the process, improving detail suppression. Watershed lines are then separated into multiple semi-lines for a further line suppression by semi-lines neighbourhood analysis. In many cases, unless a feature has a high thinness, different from image background (i.e., a thin road, in which case can be defined by a single watershed line), its representation is a set of watershed-connected lines that makes ambiguous feature-line detection for recognition of image structures. Applying watershed to the morphological gradient image, feature contouring is better characterized for waterfall application.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129975913","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
An evaluation of ensemble methods in handwritten word recognition based on feature selection 基于特征选择的手写体单词识别集成方法评价
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334133
Simon Günter, H. Bunke
{"title":"An evaluation of ensemble methods in handwritten word recognition based on feature selection","authors":"Simon Günter, H. Bunke","doi":"10.1109/ICPR.2004.1334133","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334133","url":null,"abstract":"Handwritten text recognition is one of the most difficult problems in the field of pattern recognition. The combination of multiple classifiers has been proven to be able to increase the recognition rate in difficult problems when compared to single classifiers. In this paper, several novel methods for the creation of classifier ensembles are compared where the individual classifiers use different feature subsets. The methods are evaluated in the context of handwritten word recognition, using a hidden Markov model recognizer as basic classifier.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130015905","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: 14
Connected pattern segmentation and title grouping in newspaper images 报纸图像中的连接模式分割和标题分组
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI: 10.1109/ICPR.2004.1334135
P. E. Mitchell, Hong Yan
{"title":"Connected pattern segmentation and title grouping in newspaper images","authors":"P. E. Mitchell, Hong Yan","doi":"10.1109/ICPR.2004.1334135","DOIUrl":"https://doi.org/10.1109/ICPR.2004.1334135","url":null,"abstract":"This paper presents an algorithm that performs automated segmentation and classification of newspaper images. The algorithm discusses a technique for segmenting components that are connected to other components and presents another technique to correctly group titles and subtitles. The algorithm uses a bottom-up approach to initially segment the image, classify patterns and extract text lines. The classified patterns are then merged into complete regions. The algorithm is tested on a set of complex newspaper images taken from the First International Newspaper Segmentation Contest, and the results are compared with the contest results.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130024249","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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