Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.602016
D. Olivier, B. Dominique
We present a method for segmenting multilevels images of documents. The documents are considered difficult ones in the sense they may contain text paragraphs with different orientations and shapes, mixed with graphics and photographs. The proposed method extracts and separates blocks of text lines (printed or handwritten characters) and headers as well as stroke structures. The generic approach is first based on a multiscale analysis with the use of a pyramid representation of the image. At each level, text location is performed by a line borders detection scheme. Then, an efficient bottom-up procedure generates bodies (text paragraphs) as the output of algebric transformations upon a set of four directed graphs associated with the topological relationships of physical components.
{"title":"Segmentation of complex documents multilevel images: a robust and fast text bodies-headers detection and extraction scheme","authors":"D. Olivier, B. Dominique","doi":"10.1109/ICDAR.1995.602016","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602016","url":null,"abstract":"We present a method for segmenting multilevels images of documents. The documents are considered difficult ones in the sense they may contain text paragraphs with different orientations and shapes, mixed with graphics and photographs. The proposed method extracts and separates blocks of text lines (printed or handwritten characters) and headers as well as stroke structures. The generic approach is first based on a multiscale analysis with the use of a pyramid representation of the image. At each level, text location is performed by a line borders detection scheme. Then, an efficient bottom-up procedure generates bodies (text paragraphs) as the output of algebric transformations upon a set of four directed graphs associated with the topological relationships of physical components.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"28 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133238085","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.602040
K. Romeo-Pakker, H. Miled, Y. Lecourtier
In this paper, we propose two methods of character segmentation for Arabic handwritten characters and cursive Latin characters. Classical horizontal and vertical projections detect the lowercase writing area in lines. The problem of overlapping lower or upper strokes is resolved with a contour-following algorithm which starts in the lowercase writing area and labels the detected contours. In the first method, the junction segments connecting the characters to each other are detected by taking into account the writing line thickness. The second method detects the upper contour of each word. The strokes are detected in order to find primary segmentation points (PSP). These points are analysed with an automaton that considers the shape of the word for the determination of definitive segmentation points (DSP). The two methods are compared and the results are discussed.
{"title":"A new approach for Latin/Arabic character segmentation","authors":"K. Romeo-Pakker, H. Miled, Y. Lecourtier","doi":"10.1109/ICDAR.1995.602040","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602040","url":null,"abstract":"In this paper, we propose two methods of character segmentation for Arabic handwritten characters and cursive Latin characters. Classical horizontal and vertical projections detect the lowercase writing area in lines. The problem of overlapping lower or upper strokes is resolved with a contour-following algorithm which starts in the lowercase writing area and labels the detected contours. In the first method, the junction segments connecting the characters to each other are detected by taking into account the writing line thickness. The second method detects the upper contour of each word. The strokes are detected in order to find primary segmentation points (PSP). These points are analysed with an automaton that considers the shape of the word for the determination of definitive segmentation points (DSP). The two methods are compared and the results are discussed.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133748559","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.599039
T. Bayer, H. Walischewski
Extracting structural information from paper documents supports the daily document processing by, for example, automatically finding index terms, document topics, etc. Knowledge about such components are modeled in a semantic net, which describes geometric properties, spatial relationships, lexical entities as well as lexical relationships. The document model is used to extract the sender, date, recipient, opening and closing formula from a business letter. 181 business letters have been processed, divided into a training set of 20 and the remaining ones for testing. The error rates for the test set range from 0.022 to 0.049 by an average rejection rate of 0.4. Results show that the computational effort can be limited to O(n/sup 2/) given n primitive objects for matching.
{"title":"Experiments on extracting structural information from paper documents using syntactic pattern analysis","authors":"T. Bayer, H. Walischewski","doi":"10.1109/ICDAR.1995.599039","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599039","url":null,"abstract":"Extracting structural information from paper documents supports the daily document processing by, for example, automatically finding index terms, document topics, etc. Knowledge about such components are modeled in a semantic net, which describes geometric properties, spatial relationships, lexical entities as well as lexical relationships. The document model is used to extract the sender, date, recipient, opening and closing formula from a business letter. 181 business letters have been processed, divided into a training set of 20 and the remaining ones for testing. The error rates for the test set range from 0.022 to 0.049 by an average rejection rate of 0.4. Results show that the computational effort can be limited to O(n/sup 2/) given n primitive objects for matching.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134561407","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.599027
Yung-Sheng Chen
Seal identification is usually performed by hard-matching of human visual inspection. A computer processing of the hard-matching is presented to identify a Chinese seal image. Seals of the author's own are used for experiments. Results show that the proposed approach is feasible.
{"title":"Computer processing on the identification of a Chinese seal image","authors":"Yung-Sheng Chen","doi":"10.1109/ICDAR.1995.599027","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599027","url":null,"abstract":"Seal identification is usually performed by hard-matching of human visual inspection. A computer processing of the hard-matching is presented to identify a Chinese seal image. Seals of the author's own are used for experiments. Results show that the proposed approach is feasible.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133121233","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}
Automated Chinese official document processing techniques and the public-key based cryptographic methodology are used to improve the efficiency of the existing Chinese executive information systems. They provide executive officials more room to achieve the best decision-making. One of the best solutions in document automation and message transmission is to combine low-cost computing power with stable communication capability. In this paper a computer-based architecture for intelligent Chinese official document processing is proposed. The automation of form analysis, document processing, data filing, security control, and information retrieval are discussed in detail. A digital multisignature technology is employed in this system to meet the basic requirements of data security and trust handling. By using such a technology, users will have confidence in utilizing information transmission systems without security suspicion.
{"title":"An intelligent Chinese official document processing system","authors":"Tun-Wen Pai, Tieh-Ming Wu, Gan-How Chang, Pei-Yih Ting","doi":"10.1109/ICDAR.1995.602064","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602064","url":null,"abstract":"Automated Chinese official document processing techniques and the public-key based cryptographic methodology are used to improve the efficiency of the existing Chinese executive information systems. They provide executive officials more room to achieve the best decision-making. One of the best solutions in document automation and message transmission is to combine low-cost computing power with stable communication capability. In this paper a computer-based architecture for intelligent Chinese official document processing is proposed. The automation of form analysis, document processing, data filing, security control, and information retrieval are discussed in detail. A digital multisignature technology is employed in this system to meet the basic requirements of data security and trust handling. By using such a technology, users will have confidence in utilizing information transmission systems without security suspicion.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133823570","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.601987
Myoung-Young Yoon, Seong-Whan Lee, Ju-Sung Kim
We present a new scheme for the restoration of faxed images degraded by both salient noise and additive white noise. We consider two fundamental aspects of faxed image restoration: modeling and the restoration algorithm. First, a model of a faxed image is presented. The model is based on an autoregressive Gauss-Markov random field and includes vertical and horizontal overlap effects. In particular, we concentrate on the nonsymmetric half plane causality. Second, the restoration of faxed images degraded by salient noise and additive white noise is considered by 2D Kalman filtering which provides an efficient recursive procedure. In order to illustrate the effectiveness of the proposed scheme, we present experimental results on the restoration of a faxed image.
{"title":"Faxed image restoration using Kalman filtering","authors":"Myoung-Young Yoon, Seong-Whan Lee, Ju-Sung Kim","doi":"10.1109/ICDAR.1995.601987","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601987","url":null,"abstract":"We present a new scheme for the restoration of faxed images degraded by both salient noise and additive white noise. We consider two fundamental aspects of faxed image restoration: modeling and the restoration algorithm. First, a model of a faxed image is presented. The model is based on an autoregressive Gauss-Markov random field and includes vertical and horizontal overlap effects. In particular, we concentrate on the nonsymmetric half plane causality. Second, the restoration of faxed images degraded by salient noise and additive white noise is considered by 2D Kalman filtering which provides an efficient recursive procedure. In order to illustrate the effectiveness of the proposed scheme, we present experimental results on the restoration of a faxed image.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115675755","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.599038
Debashish Niyogi, S. Srihari
The analysis of a document image to derive a symbolic description of its structure and contents involves using spatial domain knowledge to classify the different printed blocks (e.g., text paragraphs), group them into logical units (e.g., newspaper stories), and determine the reading order of the text blocks within each unit. These steps describe the conversion of the physical structure of a document into its logical structure. We have developed a computational model for document logical structure derivation, in which a rule-based control strategy utilizes the data obtained from analyzing a digitized document image, and makes inferences using a multi-level knowledge base of document layout rules. The knowledge-based document logical structure derivation system (DeLoS) based on this model consists of a hierarchical rule-based control system to guide the block classification, grouping and read-ordering operations; a global data structure to store the document image data and incremental inferences; and a domain knowledge base to encode the rules governing document layout.
{"title":"Knowledge-based derivation of document logical structure","authors":"Debashish Niyogi, S. Srihari","doi":"10.1109/ICDAR.1995.599038","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599038","url":null,"abstract":"The analysis of a document image to derive a symbolic description of its structure and contents involves using spatial domain knowledge to classify the different printed blocks (e.g., text paragraphs), group them into logical units (e.g., newspaper stories), and determine the reading order of the text blocks within each unit. These steps describe the conversion of the physical structure of a document into its logical structure. We have developed a computational model for document logical structure derivation, in which a rule-based control strategy utilizes the data obtained from analyzing a digitized document image, and makes inferences using a multi-level knowledge base of document layout rules. The knowledge-based document logical structure derivation system (DeLoS) based on this model consists of a hierarchical rule-based control system to guide the block classification, grouping and read-ordering operations; a global data structure to store the document image data and incremental inferences; and a domain knowledge base to encode the rules governing document layout.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"35 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114127740","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.601963
Jinhui Liu, Xiaoqing Ding, Youshou Wu
In this paper we present a form description method, in which frame lines are used to constitute a so-called frame template, which reflects the structure of a form either topologically or geometrically. Relevant item traversal algorithm is then proposed to locate and label form's items. We have also developed a robust and fast frame line detection method to make this form description practical for form recognition. Experimental results show our approach provides an effective way to convert printed forms into computerized format or collect information for database from printed forms.
{"title":"Description and recognition of form and automated form data entry","authors":"Jinhui Liu, Xiaoqing Ding, Youshou Wu","doi":"10.1109/ICDAR.1995.601963","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601963","url":null,"abstract":"In this paper we present a form description method, in which frame lines are used to constitute a so-called frame template, which reflects the structure of a form either topologically or geometrically. Relevant item traversal algorithm is then proposed to locate and label form's items. We have also developed a robust and fast frame line detection method to make this form description practical for form recognition. Experimental results show our approach provides an effective way to convert printed forms into computerized format or collect information for database from printed forms.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114364483","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.602080
G. Congedo, G. Dimauro, S. Impedovo, G. Pirlo
This paper presents a complete procedure for the segmentation of handwritten numeric strings. The procedure uses an hypothesis-then-verification strategy in which multiple segmentation algorithms based on contiguous row partition work sequentially on the binary image until an acceptable segmentation is obtained. At this purpose a new set of algorithms simulating a "drop falling" process is introduced. The experimental tests demonstrate the effectiveness of the new algorithms in obtaining high-confidence segmentation hypotheses.
{"title":"Segmentation of numeric strings","authors":"G. Congedo, G. Dimauro, S. Impedovo, G. Pirlo","doi":"10.1109/ICDAR.1995.602080","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602080","url":null,"abstract":"This paper presents a complete procedure for the segmentation of handwritten numeric strings. The procedure uses an hypothesis-then-verification strategy in which multiple segmentation algorithms based on contiguous row partition work sequentially on the binary image until an acceptable segmentation is obtained. At this purpose a new set of algorithms simulating a \"drop falling\" process is introduced. The experimental tests demonstrate the effectiveness of the new algorithms in obtaining high-confidence segmentation hypotheses.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117101132","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}
Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.599000
K. Gyohten, Tomoko Sumiya, N. Babaguchi, K. Kakusho, T. Kitahashi
In this paper, we present COCE (COordinative Character Extractor), a new method for extracting printed Japanese characters from an unformatted document image. This research aims to exploit knowledge independent of the layouts. COCE is based on a multiagent scheme where each agent is assigned to a single character line and tries to extract characters by making use of the knowledge about features of a character line as well as shapes and arrangement of characters. Moreover, the agents communicate with each other to keep consistency between their tasks. We have favourable results for the effectiveness of this method.
本文提出了一种从未格式化文档图像中提取打印日文字符的新方法COCE (coordinated Character Extractor)。本研究旨在开发与布局无关的知识。COCE基于多智能体方案，每个智能体被分配到单个字符线，并试图利用有关字符线的特征以及字符的形状和排列的知识来提取字符。此外，代理之间相互通信以保持其任务之间的一致性。我们对这种方法的有效性有良好的结果。
{"title":"Extracting characters and character lines in multi-agent scheme","authors":"K. Gyohten, Tomoko Sumiya, N. Babaguchi, K. Kakusho, T. Kitahashi","doi":"10.1109/ICDAR.1995.599000","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599000","url":null,"abstract":"In this paper, we present COCE (COordinative Character Extractor), a new method for extracting printed Japanese characters from an unformatted document image. This research aims to exploit knowledge independent of the layouts. COCE is based on a multiagent scheme where each agent is assigned to a single character line and tries to extract characters by making use of the knowledge about features of a character line as well as shapes and arrangement of characters. Moreover, the agents communicate with each other to keep consistency between their tasks. We have favourable results for the effectiveness of this method.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198255","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}
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