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Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition最新文献

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Class-confidence critic combining 类-自信批判组合
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030909
M. Aksela, R. Girdziusas, Jorma T. Laaksonen, E. Oja, J. Kangas
{"title":"Class-confidence critic combining","authors":"M. Aksela, R. Girdziusas, Jorma T. Laaksonen, E. Oja, J. Kangas","doi":"10.1109/IWFHR.2002.1030909","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030909","url":null,"abstract":"This paper discusses a combination of two techniques for improving the recognition accuracy of on-line handwritten character recognition: committee classification and adaptation to the user. A novel adaptive committee structure, namely the class-confidence critic combination (CCCC) scheme, is presented and evaluated. It is shown to be able to improve significantly on its member classifiers. Also the effect of having either more or less diverse sets of member classifiers is considered.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131273228","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
A comparative study on mirror image learning and ALSM 镜像学习与ALSM的比较研究
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030901
T. Wakabayashi, Meng Shi, W. Ohyama, F. Kimura
{"title":"A comparative study on mirror image learning and ALSM","authors":"T. Wakabayashi, Meng Shi, W. Ohyama, F. Kimura","doi":"10.1109/IWFHR.2002.1030901","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030901","url":null,"abstract":"In this paper, the effectiveness of a corrective learning algorithm MIL (mirror image learning) is comparatively studied with that of ALSM (average learning subspace method). Both MIL and ALSM were proposed to improve the learning effectiveness of class conditional distributions. While the ALSM modifies the basis vectors of a subspace by subtracting the autocorrelation matrix for counter classes from the one of its own class, the MIL generates a mirror image of a pattern which belongs to one of a pair of confusing classes to increases the size of the learning sample of the other class. The performance of two algorithms is evaluated on handwritten numeral recognition test for IPTP CDROMI. Experimental results show that the recognition rate of the subspace method is improved from 99.05% to 99.37% by ALSM and to 99.39% by MIL, respectively. Furthermore, the recognition rate of the projection distance method is improved from 99.13% to 99.35% by ALSM and to 99.44% by MIL.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132690359","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
A hybrid large vocabulary handwritten word recognition system using neural networks with hidden Markov models 基于隐马尔可夫模型的神经网络混合大词汇手写词识别系统
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030893
Alessandro Lameiras Koerich, Yann Leydier, R. Sabourin, C. Suen
{"title":"A hybrid large vocabulary handwritten word recognition system using neural networks with hidden Markov models","authors":"Alessandro Lameiras Koerich, Yann Leydier, R. Sabourin, C. Suen","doi":"10.1109/IWFHR.2002.1030893","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030893","url":null,"abstract":"We present a hybrid recognition system that integrates hidden Markov models (HMM) with neural networks (NN) in a probabilistic framework. The input data is processed first by a lexicon-driven word recognizer based on HMMs to generate a list of the candidate N-best-scoring word hypotheses as well as the segmentation of such word hypotheses into characters. An NN classifier is used to generate a score for each segmented character and in the end, the scores from the HMM and the NN classifiers are combined to optimize performance. Experimental results show that for an 80,000-word vocabulary, the hybrid HMM/NN system improves by about 10% the word recognition rate over the HMM system alone.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"79 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879726","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: 45
Confident assessment of children's handwritten responses 对儿童手写回答的自信评估
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030961
J. Allan, Tony Allen, N. Sherkat
{"title":"Confident assessment of children's handwritten responses","authors":"J. Allan, Tony Allen, N. Sherkat","doi":"10.1109/IWFHR.2002.1030961","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030961","url":null,"abstract":"This paper introduces a novel approach for the automatic assessment of children's responses to standardised English exam questions. The constrained nature of the question and answer medium is exploited to produce an automatic assessment mechanism that is both highly accurate and produces a reasonable level of response yield. It is shown that the novel approach can achieve 100% scoring accuracy on 44% of all responses compared to a traditional lexical approach that has an error rate of 41%. When a thresholding method, similar to that used in the novel approach is applied, the traditional approach can achieve an accuracy of 100% but with a response yield of only 5%. The approach introduced in this paper is thus shown to have a significant advantage over the traditional lexical based assessment.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134161727","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
A fast algorithm for finding k-nearest neighbors with non-metric dissimilarity 非度量不相似度的k近邻快速查找算法
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030877
Bin Zhang, S. Srihari
{"title":"A fast algorithm for finding k-nearest neighbors with non-metric dissimilarity","authors":"Bin Zhang, S. Srihari","doi":"10.1109/IWFHR.2002.1030877","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030877","url":null,"abstract":"Fast nearest neighbor (NN) finding has been extensively studied. While some fast NN algorithms using metrics rely on the essential properties of metric spaces, the others using non-metric measures fail for large-size templates. However in some applications with very large size templates, the best performance is achieved by NN methods based on the dissimilarity measures resulting in a special space where computations cannot be pruned by the algorithms based-on the triangular inequality. For such NN methods, the existing fast algorithms except condensing algorithms are not applicable. In this paper, a fast hierarchical search algorithm is proposed to find k-NNs using a non-metric measure in a binary feature space. Experiments with handwritten digit recognition show that the new algorithm reduces on average dissimilarity computations by more than 90% while losing the accuracy by less than 0.1%, with a 10% increase in memory.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132315921","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: 20
Analysis of stability in hand-written dynamic signatures 手写动态签名的稳定性分析
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030919
G. Dimauro, S. Impedovo, R. Modugno, G. Pirlo, L. Sarcinella
{"title":"Analysis of stability in hand-written dynamic signatures","authors":"G. Dimauro, S. Impedovo, R. Modugno, G. Pirlo, L. Sarcinella","doi":"10.1109/IWFHR.2002.1030919","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030919","url":null,"abstract":"This paper presents a new technique to evaluate the local stability in hand-written dynamic signatures and use the results to improve the process of automated signature verification. The experimental results points out the usefulness of integrating stability, information into the signature verification process.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"51 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114124505","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: 48
Handwritten digit recognition using state-of-the-art techniques 使用最先进技术的手写数字识别
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030930
Cheng-Lin Liu, Kazuki Nakashima, H. Sako, H. Fujisawa
{"title":"Handwritten digit recognition using state-of-the-art techniques","authors":"Cheng-Lin Liu, Kazuki Nakashima, H. Sako, H. Fujisawa","doi":"10.1109/IWFHR.2002.1030930","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030930","url":null,"abstract":"This paper presents the latest results of handwritten digit recognition on well-known image databases using the state-of-the-art feature extraction and classification techniques. The tested databases are CENPARMI, CEDAR, and MNIST. On the test dataset of each database, 56 recognition accuracies are given by combining 7 classifiers with 8 feature vectors. All the classifiers and feature vectors give high accuracies. Among the features, the chain-code feature and gradient feature show advantages, and the profile structure feature shows efficiency as a complementary feature. In comparison of classifiers, the support vector classifier with RBF kernel gives the highest accuracy but is extremely expensive in storage and computation. Among the non-SV classifiers, the polynomial classifier performs best, followed by a learning quadratic discriminant function classifier. The results are competitive compared to previous ones and they provide a baseline for evaluation of future works.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114777748","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: 48
Handwritten numeral string recognition using neural network classifier trained with negative data 用负数据训练的神经网络分类器识别手写数字字符串
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030942
Ho-Yon Kim, Kil-Taek Lim, Yun-Seok Nam
{"title":"Handwritten numeral string recognition using neural network classifier trained with negative data","authors":"Ho-Yon Kim, Kil-Taek Lim, Yun-Seok Nam","doi":"10.1109/IWFHR.2002.1030942","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030942","url":null,"abstract":"In this paper, we investigate the behavior of neural network classifiers with the negative data, and develop an off-line handwritten numeral string recognition system based on the neural network classifier that uses negative data when estimating parameters. For numeral string recognition, it is attempted to generate all plausible segmentation candidates by character segmentation, which is followed by recognizing the segmentation candidates and finding an optimal segmentation path. In the preliminary experiments for numeral string recognition, the recognition rate of the classifier trained with both positive data and negative data is much higher than the recognition rate of the classifier trained with only positive data. This is because the classifier trained with negative data produces low matching scores for noncharacters, which enables the numeral string recognizer to exclude non-characters from the segmentation alternatives, so it helps the numeral string recognizer to find correct character segmentation paths.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126668806","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
An overview and comparison of voting methods for pattern recognition 模式识别中投票方法的综述与比较
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030908
M. V. Erp, L. Vuurpijl, Lambert Schomaker
{"title":"An overview and comparison of voting methods for pattern recognition","authors":"M. V. Erp, L. Vuurpijl, Lambert Schomaker","doi":"10.1109/IWFHR.2002.1030908","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030908","url":null,"abstract":"In pattern recognition, there is a growing use of multiple classifier combinations with the goal to increase recognition performance. In many cases, plurality voting is a part of the combination process. In this article, we discuss and test several well known voting methods from politics and economics on classifier combination in order to see if an alternative to the simple plurality vote exists. We found that, assuming a number of prerequisites, better methods are available, that are comparatively simple and fast.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126286208","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: 209
Affine alignment for stroke classification 用于笔画分类的仿射对齐
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition Pub Date : 2002-08-06 DOI: 10.1109/IWFHR.2002.1030940
A. Ruiz
{"title":"Affine alignment for stroke classification","authors":"A. Ruiz","doi":"10.1109/IWFHR.2002.1030940","DOIUrl":"https://doi.org/10.1109/IWFHR.2002.1030940","url":null,"abstract":"We propose a stroke classification method based on affine alignment, appropriate for online recognition of mathematical handwriting. The method, essentially linear is simple and computationally efficient. The modeling limitations of the affine group are overcome by choosing adequate error functions and by performing alignment with respect to interpolated prototypes. So, moderate nonlinear transformations are tolerated, making the approach invariant to a wide range of handwriting deformations.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115026633","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
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