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.1995.601978
H. Hontani, S. Shimotsuji
The paper presents a new method for character string extraction that works efficiently even for a complicated geographical map. The concept of multi-scale measurement is introduced to achieve development of an efficient string detection technique. In this paper, scale means the size of the area where character candidates may exist. The proposed method first merges small black regions within a certain area into a mass. When the size of the area changes, the mass will change. The proposed method observes the change of a mass corresponding to the change of the size of the area, and searches for a stable mass as a character string. Multi-scale measurement enables the detection process to find the adequate size of an area to detect a string. Because a stable mass may include small figures, a test of the shape of a detected mass and a character recognition process follow to judge whether a mass forms a character string. If a mass is rejected, it is split into smaller masses according to the results of multi-scale measurement. These judgment and split processes are repeated to detect character strings from a pattern where several strings are written closely.
{"title":"Character detection based on multi-scale measurement","authors":"H. Hontani, S. Shimotsuji","doi":"10.1109/ICDAR.1995.601978","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601978","url":null,"abstract":"The paper presents a new method for character string extraction that works efficiently even for a complicated geographical map. The concept of multi-scale measurement is introduced to achieve development of an efficient string detection technique. In this paper, scale means the size of the area where character candidates may exist. The proposed method first merges small black regions within a certain area into a mass. When the size of the area changes, the mass will change. The proposed method observes the change of a mass corresponding to the change of the size of the area, and searches for a stable mass as a character string. Multi-scale measurement enables the detection process to find the adequate size of an area to detect a string. Because a stable mass may include small figures, a test of the shape of a detected mass and a character recognition process follow to judge whether a mass forms a character string. If a mass is rejected, it is split into smaller masses according to the results of multi-scale measurement. These judgment and split processes are repeated to detect character strings from a pattern where several strings are written closely.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"110 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":"124251932","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.1995.598985
A. Takasu, S. Satoh, E. Katsura
A syntactic rule learning method is presented for analyzing document images and constructing a database from them. This method is used in a digital library system named CyberMagazine, where document images are sequentially converted into database tuples by block segmentation, rough classification, and syntactic analysis. The syntactic rule has an ability to analyze symbols located in two dimensional plane, and has a syntax similar to an ordinal context free grammar except for the concatenation of symbols. In the presented learning method, the syntactic rules are generated from a set of parse trees by decomposing the trees according to non terminal symbols, generalizing the decomposed trees to a syntactic rule, and merging them.
{"title":"A rule learning method for academic document image processing","authors":"A. Takasu, S. Satoh, E. Katsura","doi":"10.1109/ICDAR.1995.598985","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598985","url":null,"abstract":"A syntactic rule learning method is presented for analyzing document images and constructing a database from them. This method is used in a digital library system named CyberMagazine, where document images are sequentially converted into database tuples by block segmentation, rough classification, and syntactic analysis. The syntactic rule has an ability to analyze symbols located in two dimensional plane, and has a syntax similar to an ordinal context free grammar except for the concatenation of symbols. In the presented learning method, the syntactic rules are generated from a set of parse trees by decomposing the trees according to non terminal symbols, generalizing the decomposed trees to a syntactic rule, and merging them.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"24 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":"134294853","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.1995.599008
H. Tanahashi, K. Sakaue, Kazuhiko Yamamoto
In order to develop a shape and decorative pattern database of old pottery and ceramics objects, it is necessary to obtain the surface pattern on the 3-dimensional shape of the object. This paper describes the recovery of the revolution surface from a monocular image of unknown camera parameters and the retrieval of the 2-dimensional pattern. The camera parameters are obtained by using a genetic algorithm (GA). After the revolution surfaces are reconstructed, these surfaces are developed into a 2-dimensional plane. We show that a scanner-digitized image of an old ceramic object can be analyzed by GA to reconstruct the revolution surface and to develop the 2-dimensional image on the 3-dimensional object.
{"title":"Recovering decorative patterns of ceramic objects from a monocular image using a genetic algorithm","authors":"H. Tanahashi, K. Sakaue, Kazuhiko Yamamoto","doi":"10.1109/ICDAR.1995.599008","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599008","url":null,"abstract":"In order to develop a shape and decorative pattern database of old pottery and ceramics objects, it is necessary to obtain the surface pattern on the 3-dimensional shape of the object. This paper describes the recovery of the revolution surface from a monocular image of unknown camera parameters and the retrieval of the 2-dimensional pattern. The camera parameters are obtained by using a genetic algorithm (GA). After the revolution surfaces are reconstructed, these surfaces are developed into a 2-dimensional plane. We show that a scanner-digitized image of an old ceramic object can be analyzed by GA to reconstruct the revolution surface and to develop the 2-dimensional image on the 3-dimensional object.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"23 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":"131565229","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.1995.598971
B. Wirtz
This paper presents a new technique for dynamic signature verification. A dynamic programming (DP) approach is used for function-based signature verification. Dynamic data such as pressure is treated as a function of positional data and therefore evaluated locally. Verification is based on strokes as the structural units of the signature. This global knowledge is fed into the verification procedure. The application of a 3D non-linear correlation of the signature signals uses the stroke index as the third DP index. In conjunction with the definition of a finite state automaton on the set of reference strokes the system can handle different stroke numbers, missing or additional strokes correctly. The correct alignment of matching strokes is determined simultaneously to the signature verification process; an additional alignment stage before the actual nonlinear correlation is obsolete.
{"title":"Stroke-based time warping for signature verification","authors":"B. Wirtz","doi":"10.1109/ICDAR.1995.598971","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598971","url":null,"abstract":"This paper presents a new technique for dynamic signature verification. A dynamic programming (DP) approach is used for function-based signature verification. Dynamic data such as pressure is treated as a function of positional data and therefore evaluated locally. Verification is based on strokes as the structural units of the signature. This global knowledge is fed into the verification procedure. The application of a 3D non-linear correlation of the signature signals uses the stroke index as the third DP index. In conjunction with the definition of a finite state automaton on the set of reference strokes the system can handle different stroke numbers, missing or additional strokes correctly. The correct alignment of matching strokes is determined simultaneously to the signature verification process; an additional alignment stage before the actual nonlinear correlation is obsolete.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"34 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":"131610022","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.1995.599035
A. Simon, Jean-Christophe Pret, A.P. Johnson
This paper presents a novel view of document processing, as being the reverse process to T/sub E/X. This concept simplifies the analysis of the physical structure of documents, and also suggests the use of a style file for layout recognition. An algorithm is given for both phases, layout analysis and layout recognition. The bottom-up layout analysis method employed is based on the Kruskal's algorithm and uses the distances between the components to construct the physical page structure. The algorithm is linear with respect to the number of the connected components. For layout recognition, a document style description language (DSDL) is introduced. This helps a fault-tolerant, recursive parsing algorithm to label the blocks of the document. The presented methods were designed to be used for scientific publications (papers, reports, books), but could be applied to a broader range of documents.
{"title":"(Chem)DeT/sub E/X automatic generation of a markup language description of (chemical) documents from bitmap images","authors":"A. Simon, Jean-Christophe Pret, A.P. Johnson","doi":"10.1109/ICDAR.1995.599035","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599035","url":null,"abstract":"This paper presents a novel view of document processing, as being the reverse process to T/sub E/X. This concept simplifies the analysis of the physical structure of documents, and also suggests the use of a style file for layout recognition. An algorithm is given for both phases, layout analysis and layout recognition. The bottom-up layout analysis method employed is based on the Kruskal's algorithm and uses the distances between the components to construct the physical page structure. The algorithm is linear with respect to the number of the connected components. For layout recognition, a document style description language (DSDL) is introduced. This helps a fault-tolerant, recursive parsing algorithm to label the blocks of the document. The presented methods were designed to be used for scientific publications (papers, reports, books), but could be applied to a broader range of documents.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"7 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":"133892353","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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