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2010 12th International Conference on Frontiers in Handwriting Recognition最新文献

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Personalizable Pen-Based Interface Using Lifelong Learning 个性化的基于笔的界面使用终身学习
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.37
Abdullah Almaksour, É. Anquetil, Solen Quiniou, M. Cheriet
{"title":"Personalizable Pen-Based Interface Using Lifelong Learning","authors":"Abdullah Almaksour, É. Anquetil, Solen Quiniou, M. Cheriet","doi":"10.1109/ICFHR.2010.37","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.37","url":null,"abstract":"In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system, that can be integrated into an application to provide personalization capabilities. Experiments on an on-line gesture database were performed by considering various user personalization scenarios. The experiments show that the proposed evolving gesture recognition system continuously adapts and evolve according to new data of learned classes, and remains robust when introducing new unseen classes, at any moment during the lifelong learning process.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123090625","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: 19
Error Reduction Based on Error Categorization in Arabic Handwritten Numeral Recognition 基于错误分类的阿拉伯手写体数字识别降错方法
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.125
C. He, C. Suen
{"title":"Error Reduction Based on Error Categorization in Arabic Handwritten Numeral Recognition","authors":"C. He, C. Suen","doi":"10.1109/ICFHR.2010.125","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.125","url":null,"abstract":"In practical applications, errors should not be treated equally, but conditionally. In this paper, errors are categorized based on different costs in misclassification. Accordingly, the characteristics of the error categorization and the corresponding strategies for correcting them are proposed. Verification based on Arabic Handwritten Numeral Recognition is considered as one application to utilize these definitions and strategies. As a result, the recognition results improved from 98.47% to 99.05%, and errors were significantly reduced by over 35% compared to previous studies. When a rejection measurement was applied, and the rejection threshold was adjusted to maintain the same error rate, both the recognition rate and reliability increased from 96.98% to 97.89% and from 99.08% to 99.28%, respectively.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123265049","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
Performance Analysis of the Gradient Feature and the Modified Direction Feature for Off-line Signature Verification 梯度特征和改进方向特征用于离线签名验证的性能分析
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.53
Vu Nguyen, Yumiko Kawazoe, T. Wakabayashi, U. Pal, M. Blumenstein
{"title":"Performance Analysis of the Gradient Feature and the Modified Direction Feature for Off-line Signature Verification","authors":"Vu Nguyen, Yumiko Kawazoe, T. Wakabayashi, U. Pal, M. Blumenstein","doi":"10.1109/ICFHR.2010.53","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.53","url":null,"abstract":"Feature extraction is an important process in off-line signature verification. In this work, the performance of two feature extraction techniques, the Modified Direction Feature (MDF) and the gradient feature are compared on the basis of similar experimental settings. In addition, the performance of Support Vector Machines (SVMs) and the squared Mahalanobis distance classifier employing the Gradient Feature are also compared and reported. Without using forgeries for training, experimental results indicated that an average error rate as low as 15.03% could be obtained using the gradient feature and SVMs.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123567303","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: 40
Creation of a Huge Annotated Database for Tamil and Kannada OHR 创建一个巨大的泰米尔语和卡纳达语OHR注释数据库
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.71
B. Nethravathi, P. ArchanaC., K. Shashikiran, A. Ramakrishnan, V. V. Kumar
{"title":"Creation of a Huge Annotated Database for Tamil and Kannada OHR","authors":"B. Nethravathi, P. ArchanaC., K. Shashikiran, A. Ramakrishnan, V. V. Kumar","doi":"10.1109/ICFHR.2010.71","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.71","url":null,"abstract":"This paper describes the efforts at MILE lab, IISc, to create a 100,000-word database each in Kannada and Tamil for the design and development of Online Handwritten Recognition. It has been collected from over 600 users in order to capture the variations in writing style. We describe features of the scripts and how the number of symbols were reduced to be able to effectively train the data for recognition. The list of words include all the characters, Kannada and Indo-Arabic numerals, punctuations and other symbols. A semi-automated tool for the annotation of data from stroke to word level is used. It segments each word into stroke groups and also acts as a validation mechanism for segmentation. The tool displays the stroke, stroke groups and aksharas of a word and hence can be used to study the various styles of writing, delayed strokes and for assigning quality tags to the words. The tool is currently being used for annotating Tamil and Kannada data. The output is stored in a standard XML format.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116039825","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: 40
Improving Online Handwritten Mathematical Expressions Recognition with Contextual Modeling 利用上下文建模改进在线手写数学表达式识别
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.73
Ahmad Montaser Awal, H. Mouchère, C. Viard-Gaudin
{"title":"Improving Online Handwritten Mathematical Expressions Recognition with Contextual Modeling","authors":"Ahmad Montaser Awal, H. Mouchère, C. Viard-Gaudin","doi":"10.1109/ICFHR.2010.73","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.73","url":null,"abstract":"We propose in this paper a new contextual modelling method for combining syntactic and structural information for the recognition of online handwritten mathematical expressions. Those models are used to find the most likely combination of segmentation/recognition hypotheses proposed by a 2D segment or. Models are based on structural information concerning the layouts of symbols. They are learned from a mathematical expressions dataset to prevent the use of heuristic rules which are fuzzy by nature. The system is tested with a large base of synthetic expressions and also with a set of real complex expressions.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"32 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114112031","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
Feature Extraction for Online Farsi Characters 在线波斯语字符的特征提取
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.81
V. Ghods, E. Kabir
{"title":"Feature Extraction for Online Farsi Characters","authors":"V. Ghods, E. Kabir","doi":"10.1109/ICFHR.2010.81","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.81","url":null,"abstract":"This paper demonstrates the effectiveness of proper and efficient features for classifying online Farsi characters. We use these features to classify the main body of Farsi letters to nine groups. We implemented our method on the main bodies of 4000 isolated letters from \"TMU dataset\". Correct recognition rates of 99% and 94% were achieved for training and test sets respectively.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129709923","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: 22
A Real-Time Recognition System for Handwritten Mathematics: Backtracking and Relationship Discovery 手写数学的实时识别系统:回溯和关系发现
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.69
Ray Genoe, Mohand Tahar Kechadi
{"title":"A Real-Time Recognition System for Handwritten Mathematics: Backtracking and Relationship Discovery","authors":"Ray Genoe, Mohand Tahar Kechadi","doi":"10.1109/ICFHR.2010.69","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.69","url":null,"abstract":"This paper describes a real-time approach for handwritten, mathematical expression recognition. Since users can view the output of the system after sketching each stroke, it is useful to retain as much information as possible from previous increments of an expression. However, if subsequent input results in an unordered or multi-stroke symbol, it can have adverse effects on a previously identified expression. Rather than reprocess the entire expression, it would be more beneficial to only reprocess a sub expression. To this end we have developed a backtracking technique, which can revert back to the expression discovered before this sub expression. An added benefit of this technique is that it simplifies other processes of recognition, such as relationship discovery.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129344060","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
Ontology-Based Information Extraction from Handwritten Documents 基于本体的手写文档信息提取
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.82
Sebastian Ebert, M. Liwicki, A. Dengel
{"title":"Ontology-Based Information Extraction from Handwritten Documents","authors":"Sebastian Ebert, M. Liwicki, A. Dengel","doi":"10.1109/ICFHR.2010.82","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.82","url":null,"abstract":"In this paper we introduce a new layer for the task of handwriting recognition. We add semantic information by means of ontologies. The task of our recognizer therefore is not only to recognize the ASCII transcription of the handwritten document, but also to identify the semantic concepts which appear in the text. This task is called ontology-based information extraction (OBIE), which has been applied to electronic documents recently. OBIE methods first segment the text into tokens, then identify their values and their corresponding instances of the ontology, and finally try to generate new facts based on the text. To the authors’ knowledge, in this paper OBIE is proposed for the first time in handwriting literature. In our experiments we have evaluated the process up to the instantiation. We have found that using not only the top alternative, but also the k-best alternatives increases the performance of information extraction. Furthermore, the use of an ontology-based lexicon results in another performance increase.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124201709","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
Gesture Recognition Techniques in Handwriting Recognition Application 手势识别技术在手写识别中的应用
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.29
Feng-Jun Guo, Shijie Chen
{"title":"Gesture Recognition Techniques in Handwriting Recognition Application","authors":"Feng-Jun Guo, Shijie Chen","doi":"10.1109/ICFHR.2010.29","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.29","url":null,"abstract":"Handwriting-gesture recognition has been widely implemented in handwriting input application. Usually, gestures are used to conduct edit operations or be set as short-cut of an application. In this paper, we compare several handwriting-gesture recognition methods, and address their different user cases. These methods include pixel-matching method, rule based method and discriminant-function based method. For discriminant-function based method, we describe 2 sub-methods. They are prototypes based method and training based method. We not only analyze recognition accuracy of gestures for these methods, but also analyze their distinguished capability when recognizing gestures and alphanumeric in same recognizing mode. Experiments results show that, if the gesture-samples are enough, training based method achieves the highest accuracy. Furthermore, when recognizing mixed input of gestures and other handwriting symbols, training based method almost doesn’t degrade accuracy of these symbols.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126403549","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
Identity Determination with Offline Handwritten Input Using Multi Kernel Feature Combination 基于多核特征组合的离线手写输入身份识别
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.19
Ehtesham Hassan, S. Chaudhury, M. Gopal
{"title":"Identity Determination with Offline Handwritten Input Using Multi Kernel Feature Combination","authors":"Ehtesham Hassan, S. Chaudhury, M. Gopal","doi":"10.1109/ICFHR.2010.19","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.19","url":null,"abstract":"The paper presents three novel features for handwritten data based identity recognition. A novel framework for combining the features for identification is presented. The framework combines the features in kernel space in MKL based framework. The application of features individually and in combination is presented for writer recognition and signature verification. The writer recognition results have been presented for Devanagari script input and signature verification results have been presented for open dataset [1]. The experiments have shown encouraging results.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131368612","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
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