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TS-Net: OCR Trained to Switch Between Text Transcription Styles TS-Net: OCR训练文本转录风格之间的切换
IEEE International Conference on Document Analysis and Recognition Pub Date : 2021-03-09 DOI: 10.1007/978-3-030-86337-1_32
Janina Kohut, Michal Hradiš
{"title":"TS-Net: OCR Trained to Switch Between Text Transcription Styles","authors":"Janina Kohut, Michal Hradiš","doi":"10.1007/978-3-030-86337-1_32","DOIUrl":"https://doi.org/10.1007/978-3-030-86337-1_32","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050610","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
FEDS - Filtered Edit Distance Surrogate 联邦调查局-过滤编辑距离代理
IEEE International Conference on Document Analysis and Recognition Pub Date : 2021-03-08 DOI: 10.1007/978-3-030-86337-1_12
Yash J. Patel, Jiri Matas
{"title":"FEDS - Filtered Edit Distance Surrogate","authors":"Yash J. Patel, Jiri Matas","doi":"10.1007/978-3-030-86337-1_12","DOIUrl":"https://doi.org/10.1007/978-3-030-86337-1_12","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132777579","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
Page Layout Analysis System for Unconstrained Historic Documents 无约束历史文献页面布局分析系统
IEEE International Conference on Document Analysis and Recognition Pub Date : 2021-02-23 DOI: 10.1007/978-3-030-86331-9_32
O. Kodym, Michal Hradiš
{"title":"Page Layout Analysis System for Unconstrained Historic Documents","authors":"O. Kodym, Michal Hradiš","doi":"10.1007/978-3-030-86331-9_32","DOIUrl":"https://doi.org/10.1007/978-3-030-86331-9_32","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130101021","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
SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition SPAN:用于手写段落识别的简单预测和对齐网络
IEEE International Conference on Document Analysis and Recognition Pub Date : 2021-02-17 DOI: 10.1007/978-3-030-86334-0_5
Denis Coquenet, Clément Chatelain, T. Paquet
{"title":"SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition","authors":"Denis Coquenet, Clément Chatelain, T. Paquet","doi":"10.1007/978-3-030-86334-0_5","DOIUrl":"https://doi.org/10.1007/978-3-030-86334-0_5","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462748","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
A Large Multi-target Dataset of Common Bengali Handwritten Graphemes 常见孟加拉文手写字素的大型多目标数据集
IEEE International Conference on Document Analysis and Recognition Pub Date : 2020-10-01 DOI: 10.1007/978-3-030-86337-1_26
Samiul Alam, Tahsin Reasat, Asif Sushmit, Sadi Mohammad Siddiquee, F. Rahman, Mahady Hasan, Ahmed Imtiaz Humayun
{"title":"A Large Multi-target Dataset of Common Bengali Handwritten Graphemes","authors":"Samiul Alam, Tahsin Reasat, Asif Sushmit, Sadi Mohammad Siddiquee, F. Rahman, Mahady Hasan, Ahmed Imtiaz Humayun","doi":"10.1007/978-3-030-86337-1_26","DOIUrl":"https://doi.org/10.1007/978-3-030-86337-1_26","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129969439","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: 16
LAMBERT: Layout-Aware Language Modeling for Information Extraction 面向信息抽取的布局感知语言建模
IEEE International Conference on Document Analysis and Recognition Pub Date : 2020-02-19 DOI: 10.1007/978-3-030-86549-8_34
Lukasz Garncarek, Rafal Powalski, Tomasz Stanislawek, Bartosz Topolski, Piotr Halama, M. Turski, Filip Grali'nski
{"title":"LAMBERT: Layout-Aware Language Modeling for Information Extraction","authors":"Lukasz Garncarek, Rafal Powalski, Tomasz Stanislawek, Bartosz Topolski, Piotr Halama, M. Turski, Filip Grali'nski","doi":"10.1007/978-3-030-86549-8_34","DOIUrl":"https://doi.org/10.1007/978-3-030-86549-8_34","url":null,"abstract":"","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115792853","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: 62
A syntax directed system for the recognition of printed Arabic mathematical formulas 用于识别印刷的阿拉伯数学公式的语法导向系统
IEEE International Conference on Document Analysis and Recognition Pub Date : 2015-08-23 DOI: 10.1109/ICDAR.2015.7333749
Kaouther Khazri Ayeb, A. Kacem, A. Belaïd
{"title":"A syntax directed system for the recognition of printed Arabic mathematical formulas","authors":"Kaouther Khazri Ayeb, A. Kacem, A. Belaïd","doi":"10.1109/ICDAR.2015.7333749","DOIUrl":"https://doi.org/10.1109/ICDAR.2015.7333749","url":null,"abstract":"In this paper we addressed the problem of Arabic mathematical formula recognition, extracted from scanned images of clearly printed documents. Two main stages are followed by the proposed system: symbol recognition and structural analysis of the mathematical formula. For the first stage, our system uses a combination of different statistical features like Run length, Hu and Zernike moments, Bi-level co-occurrence and white pixel's portion and an instance-based classifier K*. High accuracy for the recognition of isolated mathematical symbols is achieved. In the second stage, the system proceeds by top-down and bottom-up parsing scheme based on operator dominance. A set of replacement rules is defined by a coordinate grammar based on symbol recognition and symbol arrangement analysis results. In the proposed system, the recognition and parsing modules interact more closely. Thus, we can use the context information collected during structural analysis to help us guess about the symbols, overcoming our incorrect assumption of perfect symbol recognition. The system provides output in MathML which is easily transmitted for subsequent processing by computer algebra systems. The syntax-directed recognition system, described here, has been successfully demonstrated in many types of formulas and achieved satisfactory results. 91% of formulas are correctly recognized.","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114946484","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
Identification of Machine-Printed and Handwritten Words in Arabic and Latin Scripts 阿拉伯文和拉丁文机印字和手写字的识别
IEEE International Conference on Document Analysis and Recognition Pub Date : 2013-08-25 DOI: 10.1109/ICDAR.2013.163
Asma Saïdani, A. Kacem, A. Belaïd
{"title":"Identification of Machine-Printed and Handwritten Words in Arabic and Latin Scripts","authors":"Asma Saïdani, A. Kacem, A. Belaïd","doi":"10.1109/ICDAR.2013.163","DOIUrl":"https://doi.org/10.1109/ICDAR.2013.163","url":null,"abstract":"Our ultimate objective is to contribute to the field of script and nature identification to be able to differentiate, at word level, handwritten or machine-printed, Arabic and Latin scripts. Different sets of features have been employed successfully for discriminating between Arabic and Latin words. They include few well-established features previously used and adapted in our case and new structural features which are intrinsic features of Arabic and Latin scripts. We select features that maximize the distinction between Arabic and Latin words. Experiments have been conducted with 1320 handwritten and printed words, covering a wide range of fonts, and encouraging results have been obtained. We achieved a correct classification of 98.4 percent for word level script and nature identification using Bayes classifier.","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124528150","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: 31
Comparison of Different Preprocessing and Feature Extraction Methods for Offline Recognition of Handwritten ArabicWords 手写体阿拉伯词离线识别的预处理和特征提取方法比较
IEEE International Conference on Document Analysis and Recognition Pub Date : 2007-09-23 DOI: 10.1109/ICDAR.2007.85
H. E. Abed, V. Märgner
{"title":"Comparison of Different Preprocessing and Feature Extraction Methods for Offline Recognition of Handwritten ArabicWords","authors":"H. E. Abed, V. Märgner","doi":"10.1109/ICDAR.2007.85","DOIUrl":"https://doi.org/10.1109/ICDAR.2007.85","url":null,"abstract":"Preprocessing and feature extraction are very important steps in automatic cursive handwritten word recognition. Based on an offline recognition system for Arabic handwritten words which uses a semi-continuous 1-dimensional Hidden Markov Model recognizer, different preprocessing combined with different feature sets are presented. The dependencies of the feature sets from preprocessing steps are discussed and their performances are compared using the IFN/ENIT-database of handwritten Arabic words. As the lower and upper baseline of each word are part of the ground truth of the database, the dependency of the feature set from the accuracy of the estimated baseline is evaluated.","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126904198","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: 67
An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform 基于Contourlet变换的多字体阿拉伯字符特征提取方法
IEEE International Conference on Document Analysis and Recognition Pub Date : 2007-09-23 DOI: 10.1109/ICDAR.2007.45
N. Amor, N. Amara
{"title":"An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform","authors":"N. Amor, N. Amara","doi":"10.1109/ICDAR.2007.45","DOIUrl":"https://doi.org/10.1109/ICDAR.2007.45","url":null,"abstract":"In this paper, we propose a method for features extraction from multifont Arabic characters images based on the Contourlet Transform, which has been recently introduced. In our previous works, we noticed that Wavelet transforms are not capable of reconstructing curved images perfectly; the Contourlet Transform offers a solution to remedy to this insufficiency. It allows a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet Transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Experimental tests have been carried out on a set of 175.000 samples of characters corresponding to 9 different Arabic fonts. Some promising experimental results are reported.","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115916249","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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