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2014 11th IAPR International Workshop on Document Analysis Systems最新文献

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Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images 结合焦点测量算子预测移动捕获文档图像OCR精度
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.11
Marçal Rusiñol, J. Chazalon, J. Ogier
{"title":"Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images","authors":"Marçal Rusiñol, J. Chazalon, J. Ogier","doi":"10.1109/DAS.2014.11","DOIUrl":"https://doi.org/10.1109/DAS.2014.11","url":null,"abstract":"Mobile document image acquisition is a new trend raising serious issues in business document processing workflows. Such digitization procedure is unreliable, and integrates many distortions which must be detected as soon as possible, on the mobile, to avoid paying data transmission fees, and losing information due to the inability to re-capture later a document with temporary availability. In this context, out-of-focus blur is major issue: users have no direct control over it, and it seriously degrades OCR recognition. In this paper, we concentrate on the estimation of focus quality, to ensure a sufficient legibility of a document image for OCR processing. We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on document images, which are fast to compute and require no training. Second, we show that a combination of those measures enables state-of-the art performance regarding the correlation with OCR accuracy. The resulting approach is fast, robust, and easy to implement in a mobile device. Experiments are performed on a public dataset, and precise details about image processing are given.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199969","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: 36
A Novel Learning-Free Word Spotting Approach Based on Graph Representation 一种新的基于图表示的免学习词识别方法
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.46
P. Wang, V. Eglin, Christophe Garcia, C. Largeron, J. Lladós, A. Fornés
{"title":"A Novel Learning-Free Word Spotting Approach Based on Graph Representation","authors":"P. Wang, V. Eglin, Christophe Garcia, C. Largeron, J. Lladós, A. Fornés","doi":"10.1109/DAS.2014.46","DOIUrl":"https://doi.org/10.1109/DAS.2014.46","url":null,"abstract":"Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132351589","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: 39
A Seed-Based Segmentation Method for Scene Text Extraction 一种基于种子的场景文本分割方法
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.34
Bo Bai, Fei Yin, Cheng-Lin Liu
{"title":"A Seed-Based Segmentation Method for Scene Text Extraction","authors":"Bo Bai, Fei Yin, Cheng-Lin Liu","doi":"10.1109/DAS.2014.34","DOIUrl":"https://doi.org/10.1109/DAS.2014.34","url":null,"abstract":"Scene text extraction, i.e., segmenting text pixels from background, is an important step before the text can be recognized. It is a challenging problem due to the cluttered background and the variation of lighting. In this paper, we propose a seed-based segmentation method that can automatically judge the text polarity, extract seed points of text and background, and segment texts by semi-supervised learning (SSL). First, we estimate the text polarity and the stroke width using gradient local correlation. Then, all the points in the middle of stroke edge pairs satisfying the width and polarity are taken as foreground seeds, and the points in the middle of the edge pairs with opposite polarity are taken as background seeds. The whole image is then segmented into text and background using an SSL algorithm. Owing to the accurate estimate of text polarity and extraction of seed points, the proposed method yields good segmentation performance. Experimental results on the KAIST dataset demonstrate the superiority of the method.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121773285","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
Historical Chinese Character Recognition Method Based on Style Transfer Mapping 基于风格迁移映射的历史汉字识别方法
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.33
Bohan Li, Liangrui Peng, Jingning Ji
{"title":"Historical Chinese Character Recognition Method Based on Style Transfer Mapping","authors":"Bohan Li, Liangrui Peng, Jingning Ji","doi":"10.1109/DAS.2014.33","DOIUrl":"https://doi.org/10.1109/DAS.2014.33","url":null,"abstract":"Historical Chinese character recognition has been a challenging topic in pattern recognition field because of large character set, various writing styles and lack of training samples. In this paper, we adopted Style Transfer Mapping (STM) method to historical Chinese character recognition. Optimal selection of parameters was discussed. Two sets of experiments were conducted. The first set of experiment was designed to test the performance of STM on different font styles by using available printed traditional Chinese characters. The second set of experiment was carried out on samples extracted from practical historical Chinese documents. Experimental results showed that supervised STM may improve the generalization ability of the classifier.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884742","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
Ground-Truth Production in the Transcriptorium Project 转录项目中的真实生产
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.23
B. Gatos, G. Louloudis, T. Causer, Kris Grint, Verónica Romero, Joan Andreu Sánchez, A. Toselli, E. Vidal
{"title":"Ground-Truth Production in the Transcriptorium Project","authors":"B. Gatos, G. Louloudis, T. Causer, Kris Grint, Verónica Romero, Joan Andreu Sánchez, A. Toselli, E. Vidal","doi":"10.1109/DAS.2014.23","DOIUrl":"https://doi.org/10.1109/DAS.2014.23","url":null,"abstract":"Tran Scriptorium is a 3-years project that aims to develop innovative, cost-effective solutions for the indexing, search and full transcription of historical handwritten document images, using Handwritten Text Recognition (HTR) technology. The production of ground-truth (GT) of a dataset of handwritten document images is among the first tasks. We address novel approaches for the faster production of this GT based on crowd-sourcing and on prior-knowledge methods. We also address here a novel low-cost semi-supervised procedure for obtaining pairs of correct line-level aligned detected/extracted text line images and text line transcripts, specially suitable for training models of the HTR technology employed in Tran Scriptorium.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114019041","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: 39
The A2iA Arabic Handwritten Text Recognition System at the Open HaRT2013 Evaluation A2iA阿拉伯语手写文本识别系统在Open HaRT2013的评估
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.40
Théodore Bluche, J. Louradour, Maxime Knibbe, Bastien Moysset, Mohamed Benzeghiba, Christopher Kermorvant
{"title":"The A2iA Arabic Handwritten Text Recognition System at the Open HaRT2013 Evaluation","authors":"Théodore Bluche, J. Louradour, Maxime Knibbe, Bastien Moysset, Mohamed Benzeghiba, Christopher Kermorvant","doi":"10.1109/DAS.2014.40","DOIUrl":"https://doi.org/10.1109/DAS.2014.40","url":null,"abstract":"This paper describes the Arabic handwriting recognition systems proposed by A2iA to the NIST OpenHaRT2013 evaluation. These systems were based on an optical model using Long Short-Term Memory (LSTM) recurrent neural networks, trained to recognize the different forms of the Arabic characters directly from the image, without explicit feature extraction nor segmentation.Large vocabulary selection techniques and n-gram language modeling were used to provide a full paragraph recognition, without explicit word segmentation. Several recognition systems were also combined with the ROVER combination algorithm. The best system exceeded 80% of recognition rate.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127162679","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
Color Descriptor for Content-Based Drawing Retrieval 基于内容的绘图检索的颜色描述符
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.70
Christophe Rigaud, Dimosthenis Karatzas, J. Burie, J. Ogier
{"title":"Color Descriptor for Content-Based Drawing Retrieval","authors":"Christophe Rigaud, Dimosthenis Karatzas, J. Burie, J. Ogier","doi":"10.1109/DAS.2014.70","DOIUrl":"https://doi.org/10.1109/DAS.2014.70","url":null,"abstract":"Human detection in computer vision field is an active field of research. Extending this to human-like drawings such as the main characters in comic book stories is not trivial. Comics analysis is a very recent field of research at the intersection of graphics, texts, objects and people recognition. The detection of the main comic characters is an essential step towards a fully automatic comic book understanding. This paper presents a color-based approach for comics character retrieval using content-based drawing retrieval and color palette.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124558210","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 New Laplacian Method for Arbitrarily-Oriented Word Segmentation in Video 视频中任意方向分词的拉普拉斯新方法
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.21
P. Shivakumara, M. Suhil, D. S. Guru, C. Tan
{"title":"A New Laplacian Method for Arbitrarily-Oriented Word Segmentation in Video","authors":"P. Shivakumara, M. Suhil, D. S. Guru, C. Tan","doi":"10.1109/DAS.2014.21","DOIUrl":"https://doi.org/10.1109/DAS.2014.21","url":null,"abstract":"Word segmentation from video text line is challenging because video poses several challenges, such as complex background, low resolution, arbitrary orientation, etc. Besides, word segmentation is essential for improving text recognition accuracy. Therefore, we propose a novel method for segmenting words by exploring zero crossing points for each sliding window over text line. The candidate zero crossing pointes are defined based on characteristics of positive and negative Laplacian values at text region and non-text region. The percentage of candidate zero crossing points is calculated for each sliding window and is used for identifying the seed window that represents space between words. For the seed window, we propose a novel idea of horizontal and vertical sampling based on the percentage values to estimate the width and the height of the word spacing. Then the width and the height of the word spacing are used to validate the actual word spacing. Experimental results comparing with an existing method show that the proposed method is better than the existing method in terms of recall, precision and f-measure on curved, horizontal, non-horizontal, Hua's video data, as well as ICDAR data. We also test it on our own data containing multiscript text lines to show the robustness of the proposed method.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122746581","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
Evaluation of Texture Features for Offline Arabic Writer Identification 离线阿拉伯语作家识别的纹理特征评价
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.76
Chawki Djeddi, L. Souici-Meslati, I. Siddiqi, A. Ennaji, H. E. Abed, A. Gattal
{"title":"Evaluation of Texture Features for Offline Arabic Writer Identification","authors":"Chawki Djeddi, L. Souici-Meslati, I. Siddiqi, A. Ennaji, H. E. Abed, A. Gattal","doi":"10.1109/DAS.2014.76","DOIUrl":"https://doi.org/10.1109/DAS.2014.76","url":null,"abstract":"Biometric identification of persons has mainly been based on fingerprints, face, iris and other similar attributes. We propose a handwriting-based biometric identification system using a large database of Arabic handwritten documents. The system first extracts, from each handwritten sample, a set of features including run lengths, edge-hinge and edge-direction features. These features are used by a Multiclass SVM (Support Vector Machine) classifier. Experiments are conducted on a new large database of Arabic handwritings contributed by 1000 writers. The highest identification rate achieved by the combination of run-length and edge-hinge features stands at 84.10%.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131035573","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
A Context Based Text Summarization System 基于上下文的文本摘要系统
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.19
Rafael Ferreira, F. Freitas, L. Cabral, R. Lins, Rinaldo Lima, G. Silva, S. Simske, Luciano Favaro
{"title":"A Context Based Text Summarization System","authors":"Rafael Ferreira, F. Freitas, L. Cabral, R. Lins, Rinaldo Lima, G. Silva, S. Simske, Luciano Favaro","doi":"10.1109/DAS.2014.19","DOIUrl":"https://doi.org/10.1109/DAS.2014.19","url":null,"abstract":"Text summarization is the process of creating a shorter version of one or more text documents. Automatic text summarization has become an important way of finding relevant information in large text libraries or in the Internet. Extractive text summarization techniques select entire sentences from documents according to some criteria to form a summary. Sentence scoring is the technique most used for extractive text summarization, today. Depending on the context, however, some techniques may yield better results than some others. This paper advocates the thesis that the quality of the summary obtained with combinations of sentence scoring methods depend on text subject. Such hypothesis is evaluated using three different contexts: news, blogs and articles. The results obtained show the validity of the hypothesis formulated and point at which techniques are more effective in each of those contexts studied.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556719","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: 61
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