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

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Word-Wise Handwritten Persian and Roman Script Identification Word-Wise手写波斯语和罗马文字识别
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.103
K. Roy, Alireza Alaei, U. Pal
{"title":"Word-Wise Handwritten Persian and Roman Script Identification","authors":"K. Roy, Alireza Alaei, U. Pal","doi":"10.1109/ICFHR.2010.103","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.103","url":null,"abstract":"Most of the countries use bi-script documents. This is because every country uses its own national language and English as second/foreign language. Therefore, bi-lingual document with one language being the English and other being the national language is very common. Postal documents are a very good example of such bi-lingual/script document. This paper deals with word-wise handwritten script identification from bi-script documents written in Persian and Roman. In the proposed scheme, simple but fast computable set of 12 features based on fractal dimension, position of small component, topology etc. are used and a set of classifiers are employed for script identification experiments. We tested our scheme on a dataset of 5000 handwritten Persian and English words and 99.20% of correct script identification is obtained.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"284 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":"122674015","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: 27
Recognition of Hand-Drawn Graphs Using Digital-Geometric Techniques 利用数字几何技术识别手绘图形
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.20
Sanjoy Pratihar, Shyamosree Pal, Partha Bhowmick, A. Biswas, B. Bhattacharya
{"title":"Recognition of Hand-Drawn Graphs Using Digital-Geometric Techniques","authors":"Sanjoy Pratihar, Shyamosree Pal, Partha Bhowmick, A. Biswas, B. Bhattacharya","doi":"10.1109/ICFHR.2010.20","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.20","url":null,"abstract":"A novel algorithm to recognize hand-drawn graphs is proposed. The algorithm uses properties of digital-geometric straightness combined with a new idea of Farey sequence, followed by geometric refinement, in order to speed up the recognition of graph edges. In the next phase, the nodes of the graph — which, being hand-drawn, are very grossly circular — are recognized using the annular regions containing the vertices of their corresponding isothetic covers. Results of the two phases are finally compiled using interval search to output the adjacency list of the graph. The problems of jaggedness, waviness, and similar unforeseen aberrations usually present in a hand-drawn graph are well-tackled by the adopted techniques, as verified by our experimentation on various hand-drawn graphs. Some results have been given in this paper to show the usability and efficiency of the proposed algorithm.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"51 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":"123054565","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
Reading Cursive Handwriting 阅读草书
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.21
C. Stefano, A. Marcelli, Antonio Parziale, R. Senatore
{"title":"Reading Cursive Handwriting","authors":"C. Stefano, A. Marcelli, Antonio Parziale, R. Senatore","doi":"10.1109/ICFHR.2010.21","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.21","url":null,"abstract":"We present a method for off-line reading of cursive handwriting, which derives from modelling handwriting as a complex movement. The method includes a step for recovering the writing order from static images of handwriting, a segmentation algorithm that decomposes the “unfolded” ink into strokes, an ink matching step to compare the ink of the unknown handwriting with those of a set of reference words, of whom the transcripts are given, and a graph search algorithm to search for the best interpretation among the possible ones. The method does not involve any feature extraction, nor a classification stage and may benefit from a linguistic context, if available. We report the results of experiments on 8,000 samples, draw some conclusions and outline further developments.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"13 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":"123675067","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: 15
Selecting Features Using the SFS in Conjunction with Vector Quantization 结合矢量量化使用SFS选择特征
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.80
J. Schenk, G. Rigoll
{"title":"Selecting Features Using the SFS in Conjunction with Vector Quantization","authors":"J. Schenk, G. Rigoll","doi":"10.1109/ICFHR.2010.80","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.80","url":null,"abstract":"When discrete Hidden-Markov-Models (HMMs)-based recognition is performed, vector quantization (VQ) is used to transform continuous observations to sequences of discrete symbols. After VQ, the quantization error is not spread equally among the features. This impairs the feature significance, which is important when features are selected, e. g. by applying the Sequential Forward Selection (SFS). In this paper, we introduce a novel vector quantization (VQ) scheme for distributing the quantization error equally among the quantized dimensions of a feature vector. Afterwards, the proposed VQ scheme is used to apply the SFS on the features in on-line handwritten whiteboard note recognition based on discrete HMMs. In an experimental section, we show that the novel VQ scheme derives feature sets of almost half the size of the feature sets gained when standard VQ is used for quantization, while the performance stays the same.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"30 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":"126753442","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
Document-Zone Classification in Torn Documents 撕裂文档中的文档区域分类
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.12
S. Chanda, K. Franke, U. Pal
{"title":"Document-Zone Classification in Torn Documents","authors":"S. Chanda, K. Franke, U. Pal","doi":"10.1109/ICFHR.2010.12","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.12","url":null,"abstract":"Arbitrary orientation and sparse data content are common characteristics of torn document. To ensure accuracy and reliability in computer-based analysis, content-zone segmentation is required. In our previous work, we studied segmentation of handwritten and printed text. A questioned document-piece in the form of an office note, however, might also contain non-text data like logos, graphics, and pictures. Hence a more precise content-zone classification is required. In this paper we propose a two-tier approach for non-text, handwriting and printed text segmentation. The first tier aims to discriminate text and non-text regions. The second tier classifies handwritten and printed text within all text zones identified during the first tier. Gabor features and chain-code features are used in Tier-1 and Tier-2, respectively. By using SVM classifier we successfully identified 97.65% of 31,227 text regions in our current test data. The proposed approach identified 98.69% of printed and 96.39% of handwritten text amongst all identified text regions.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"42 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":"121582451","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
Orthogonal LDA in PCA Transformed Subspace PCA变换子空间中的正交LDA
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.34
M. Prasad, M. Sukumar, A. Ramakrishnan
{"title":"Orthogonal LDA in PCA Transformed Subspace","authors":"M. Prasad, M. Sukumar, A. Ramakrishnan","doi":"10.1109/ICFHR.2010.34","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.34","url":null,"abstract":"The paper addresses the effectiveness of orthogonal linear discriminant analysis (OLDA) in a principal component analysis (PCA) transformed subspace. The performance of the technique is studied for writer independent recognition of online handwritten Kannada numerals. Experiments show that the performance of LDA and OLDA are better in a PCA transformed subspace compared to that of the original feature space. In addition, the recognition accuracies of the system with OLDA are marginally better than that of LDA in both the original feature space and the PCA transformed subspace. An average recognition accuracy of 96.9% is achieved on a database collected from 69 writers. To our knowledge, this is the first ever reported work on recognition of online handwritten Kannada numerals.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"337 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":"124310220","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
Retrieving Handwriting Styles: A Content Based Approach to Handwritten Document Retrieval 检索手写样式:基于内容的手写文档检索方法
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.48
Anurag Bhardwaj, A. Thomas, Yun Fu, V. Govindaraju
{"title":"Retrieving Handwriting Styles: A Content Based Approach to Handwritten Document Retrieval","authors":"Anurag Bhardwaj, A. Thomas, Yun Fu, V. Govindaraju","doi":"10.1109/ICFHR.2010.48","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.48","url":null,"abstract":"Large scale retrieval of handwritten documents has primarily been focused around searching a query text in the OCR’ed transcription of the document images, which provides a limited view of the complete search process. Recent research advances have led to a number of content based retrieval techniques which expand the search scope to document content level (i.e. image features, meta-information). Based on similar motivations, we propose a new approach to content based retrieval of handwritten document images by retrieving similar handwriting styles corresponding to a handwritten query image. At the core, we formulate this problem as the task of unsupervised writer style classification without the need of any style definitions or grammar. We build upon our previous work in writer style modeling and apply it to learn a style distribution for every handwriting sample in the corpus. Given a query image, all documents are ranked in order of their style distribution similarity. Experimental results conducted on publicly available IAM dataset demonstrate the efficacy of our proposed method over baseline feature based systems.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"9 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":"122126340","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
A Model Based Text Line Segmentation Method for Off-line Handwritten Documents 基于模型的离线手写文档文本线分割方法
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.26
J. D. Gupta, B. Chanda
{"title":"A Model Based Text Line Segmentation Method for Off-line Handwritten Documents","authors":"J. D. Gupta, B. Chanda","doi":"10.1109/ICFHR.2010.26","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.26","url":null,"abstract":"Text line segmentation is one of the important steps for offline handwritten text / handwriting recognition. This paper describes a novel method of text line segmentation based on the physical process of writing. The basic concept behind this segmentation method is: two successive handwritten text-line are always non-intersecting. The proof of the theory is explained with a model of pen-tip movement. The line segmentation is done by arranging the centroids of connected components present in the given text document. Experiments show that the proposed method achieves high accuracy for detecting unconstrained text line of handwritten documents.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"50 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":"116805585","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
Accented Handwritten Character Recognition Using SVM - Application to French 使用SVM的重音手写字符识别-在法语中的应用
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.16
De Cao Tran, P. Franco, J. Ogier
{"title":"Accented Handwritten Character Recognition Using SVM - Application to French","authors":"De Cao Tran, P. Franco, J. Ogier","doi":"10.1109/ICFHR.2010.16","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.16","url":null,"abstract":"This paper deals with the problem of recognizing accented and non-accented characters in French handwriting. Accented characters increase the number of classes to be recognized. The performances of powerful classifier such as SVM are declined by the presence of accents. In this paper, an accented character is segmented into two parts: the root character or letter and the accent. These two parts are recognized separately, and the results are combined to rebuild the accented character. This approach avoids the combination of characters and accents that causes an increase in the number of classes to be considered. For handwritten character recognition, the combination of on-line and off-line features is used. The paper illustrates that French accented and non-accented characters and digits can be described by a combination of this kind of data. Moreover, the number of features of the combination is not necessarily very high. The experimental investigations show that the handwritten character recognition built on 45 selected features can compete with recognition rate and response time of other well known tested on standard databases such as UNIPEN and IRONOFF.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"132 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":"117278779","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
Verification of Unconstrained Handwritten Words at Character Level 字符级无约束手写单词的验证
2010 12th International Conference on Frontiers in Handwriting Recognition Pub Date : 2010-11-16 DOI: 10.1109/ICFHR.2010.14
Alessandro Lameiras Koerich, A. Britto, Luiz Oliveira
{"title":"Verification of Unconstrained Handwritten Words at Character Level","authors":"Alessandro Lameiras Koerich, A. Britto, Luiz Oliveira","doi":"10.1109/ICFHR.2010.14","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.14","url":null,"abstract":"In this paper we present a verification module that has as input the output provided by a word recognizer which is based on the segmentation-recognition paradigm. The word recognizer models words as the concatenation of character hidden Markov models (HMMs) and it provides at the output a list with the Top N best word hypotheses, including their likelihoods and the segmentation points of the words into sub words, which ideally should be characters. The verification module uses the segmentation points provided by the word recognizer for each word hypothesis to extract different features from each sub word. A classifier based on a multilayer perceptron neural network assigns a character class (A-Z) and estimates the a posteriori probability to each sub word that make up a word. Further, both the character class and the a posteriori probabilities are combined with the original output of the word recognizer to re-rank the word hypothesis into the Top N list. Experimental results show that the verification module improves the Top 1 recognition rate in 3.9% for an 85,092-word recognition task.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"1 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":"128825401","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
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