Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.598941
Hui Su, Wei Wang, Xinyou Li, Shaowei Xia
The similarity degree of hand-written characters in engineering drawings is analyzed. On the basis of the results, a hierarchical neural network is proposed for recognizing hand-written characters in engineering drawings. In a hierarchical neural network the memorizing and recognizing procedure is distributed into several subnetworks. Experimental results are also given.
{"title":"Hierarchical neural network for recognizing hand-written characters in engineering drawings","authors":"Hui Su, Wei Wang, Xinyou Li, Shaowei Xia","doi":"10.1109/ICDAR.1995.598941","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598941","url":null,"abstract":"The similarity degree of hand-written characters in engineering drawings is analyzed. On the basis of the results, a hierarchical neural network is proposed for recognizing hand-written characters in engineering drawings. In a hierarchical neural network the memorizing and recognizing procedure is distributed into several subnetworks. Experimental results are also given.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"32 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133076168","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.1995.598933
D. Guillevic, C. Suen
A method for recognizing unconstrained handwritten words belonging to a small static lexicon is proposed. Our computational theory is based on a psychological model of the reading process of a fast reader. The method we propose is global in its nature and avoid the difficult segmentation stage of common word recognition techniques. Our computational theory has been applied to the processing of handwritten bank cheques, whose problem domain is that of unconstrained handwriting, unlimited writers in a small static lexicon. Current results seem comparable to those published in the literature and support our computational theory.
{"title":"Cursive script recognition applied to the processing of bank cheques","authors":"D. Guillevic, C. Suen","doi":"10.1109/ICDAR.1995.598933","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598933","url":null,"abstract":"A method for recognizing unconstrained handwritten words belonging to a small static lexicon is proposed. Our computational theory is based on a psychological model of the reading process of a fast reader. The method we propose is global in its nature and avoid the difficult segmentation stage of common word recognition techniques. Our computational theory has been applied to the processing of handwritten bank cheques, whose problem domain is that of unconstrained handwriting, unlimited writers in a small static lexicon. Current results seem comparable to those published in the literature and support our computational theory.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"91 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":"133694039","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.1995.602120
F. Cesarini, M. Gori, S. Marinai, G. Soda
In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on attributed relational graphs and the system performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. A special emphasis has been placed at the low level, where an autoassociator-based connectionist model has exhibited successful results in finding the instruction fields in very noisy forms.
{"title":"A system for data extraction from forms of known class","authors":"F. Cesarini, M. Gori, S. Marinai, G. Soda","doi":"10.1109/ICDAR.1995.602120","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602120","url":null,"abstract":"In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on attributed relational graphs and the system performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. A special emphasis has been placed at the low level, where an autoassociator-based connectionist model has exhibited successful results in finding the instruction fields in very noisy forms.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"27 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":"133335034","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.1995.601977
A. Braun, T. Caesar, J. Gloger, E. Mandler
In a binary image contours may be seen as the discriminating curve between objects and background. Contours of connected components are always a Jordan curve. One symbol (e.g., a character) may consist of more than one such curve. Processing these curves is a one-dimensional task. Almost all common processing steps can be designed to work on contours rather than on the two-dimensional image. Moreover, contour processing gives new insight to well know problems and enables new processing steps or produces more information about the relations between connected components or objects of the image. The authors present preprocessing operations which work directly on the level of contours. Compared to the corresponding iconic operations, algorithms working on the contour level are mostly more efficient. Based on the contours of the connected components methods for filtering and slant normalization are described.
{"title":"Preprocessing raw binary images by means of contours","authors":"A. Braun, T. Caesar, J. Gloger, E. Mandler","doi":"10.1109/ICDAR.1995.601977","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601977","url":null,"abstract":"In a binary image contours may be seen as the discriminating curve between objects and background. Contours of connected components are always a Jordan curve. One symbol (e.g., a character) may consist of more than one such curve. Processing these curves is a one-dimensional task. Almost all common processing steps can be designed to work on contours rather than on the two-dimensional image. Moreover, contour processing gives new insight to well know problems and enables new processing steps or produces more information about the relations between connected components or objects of the image. The authors present preprocessing operations which work directly on the level of contours. Compared to the corresponding iconic operations, algorithms working on the contour level are mostly more efficient. Based on the contours of the connected components methods for filtering and slant normalization are described.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"439 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":"133453488","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.1995.601994
H. Nishida
An essential problem in handwriting recognition is how to cope with complex shape deformation, and therefore, the modeling of the deformation and its metamorphosis (transformation of an instance of a class into an instance of the other class via continuous transformation) is a key to breaking through the difficulties in handwriting recognition. Based on the structural feature extraction and description by Nishida (1995), we present a model for structural deformation with simple, local operations that preserve the global structure of the shape. Furthermore, we present an experimental approach to the analysis of metamorphosis of character shapes based on the structural deformation model.
{"title":"A structural model of continuous transformation of handwritten characters","authors":"H. Nishida","doi":"10.1109/ICDAR.1995.601994","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601994","url":null,"abstract":"An essential problem in handwriting recognition is how to cope with complex shape deformation, and therefore, the modeling of the deformation and its metamorphosis (transformation of an instance of a class into an instance of the other class via continuous transformation) is a key to breaking through the difficulties in handwriting recognition. Based on the structural feature extraction and description by Nishida (1995), we present a model for structural deformation with simple, local operations that preserve the global structure of the shape. Furthermore, we present an experimental approach to the analysis of metamorphosis of character shapes based on the structural deformation model.","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":"132141851","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.1995.602078
R. Casey, É. Lecolinet
This paper provides a review of advances in character segmentation. Segmentation methods are listed under four main headings. The operation of attempting to decompose the image into classifiable units on the basis of general image features is called "dissection". The second class of methods avoids dissection, and segments the image either explicitly, by classification of specified windows, or implicitly by classification of subsets of spatial features collected from the image as a whole. The third strategy is a hybrid of the first two, employing dissection together with recombination rules to define potential segments, but using classification to select from the range of admissible segmentation possibilities offered by these subimages. Finally, holistic approaches that avoid segmentation by recognizing entire character strings as units are described.
{"title":"Strategies in character segmentation: a survey","authors":"R. Casey, É. Lecolinet","doi":"10.1109/ICDAR.1995.602078","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602078","url":null,"abstract":"This paper provides a review of advances in character segmentation. Segmentation methods are listed under four main headings. The operation of attempting to decompose the image into classifiable units on the basis of general image features is called \"dissection\". The second class of methods avoids dissection, and segments the image either explicitly, by classification of specified windows, or implicitly by classification of subsets of spatial features collected from the image as a whole. The third strategy is a hybrid of the first two, employing dissection together with recombination rules to define potential segments, but using classification to select from the range of admissible segmentation possibilities offered by these subimages. Finally, holistic approaches that avoid segmentation by recognizing entire character strings as units are described.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"61 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":"134472348","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.1995.602061
K. Kise, Noriyoshi Yoneda, S. Takamatsu, K. Fukunaga
A conceptual diagram is a kind of diagram which represents a logical structure among concepts using simple physical objects (loops, lines and character strings). This paper presents a method of interpretation of conceptual diagrams. In conceptual diagrams, a single physical object plays various logical roles depending on surrounding physical objects, because there are no specific ruled of writing conceptual diagrams. To cope with this problem, we introduce the strategy of hypothesis generation and verification; hypothesized interpretations are verified by relaxation which takes account of logical relations to other physical objects. From the experimental results using 50 conceptual diagrams, we discuss the effectiveness of our method.
{"title":"Interpretation of conceptual diagrams from line segments and strings","authors":"K. Kise, Noriyoshi Yoneda, S. Takamatsu, K. Fukunaga","doi":"10.1109/ICDAR.1995.602061","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602061","url":null,"abstract":"A conceptual diagram is a kind of diagram which represents a logical structure among concepts using simple physical objects (loops, lines and character strings). This paper presents a method of interpretation of conceptual diagrams. In conceptual diagrams, a single physical object plays various logical roles depending on surrounding physical objects, because there are no specific ruled of writing conceptual diagrams. To cope with this problem, we introduce the strategy of hypothesis generation and verification; hypothesized interpretations are verified by relaxation which takes account of logical relations to other physical objects. From the experimental results using 50 conceptual diagrams, we discuss the effectiveness of our method.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"9 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":"131327926","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.1995.602033
Alexander Filatov, Alexander Gitis, Igor Kil
The article presents a handwritten digit string recognition algorithm based on matching input subgraphs with prototype symbol graphs. The article defines a set of acceptable graph transformations corresponding to typical variations of the handwritten symbols. The search for a match between the input subgraph and prototype graph is conducted using this set of transformations. This approach allows us to solve the problems of structure recognition methods caused by a high variability of handwritten symbol topology. The article presents experimental results of the handwritten digit string recognition system.
{"title":"Graph-based handwritten digit string recognition","authors":"Alexander Filatov, Alexander Gitis, Igor Kil","doi":"10.1109/ICDAR.1995.602033","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602033","url":null,"abstract":"The article presents a handwritten digit string recognition algorithm based on matching input subgraphs with prototype symbol graphs. The article defines a set of acceptable graph transformations corresponding to typical variations of the handwritten symbols. The search for a match between the input subgraph and prototype graph is conducted using this set of transformations. This approach allows us to solve the problems of structure recognition methods caused by a high variability of handwritten symbol topology. The article presents experimental results of the handwritten digit string recognition system.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"80 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":"131912033","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.1995.602055
O. Shiku, A. Nakamura, Masanori Anegawa, Hideaki Takahira, H. Kuroda
The paper proposes a method for extracting slant characters from complicated background figures efficiently and rapidly. In this method, slant character candidates are extracted using the black pixel density features, that is, matching rate of two different sized circular templates, which are inscribing and circumscribing a target character, with an original image. In order to estimate performance of the proposed method, the method was applied to 41 topographic map images (512/spl times/512 pixels) involving 1032 slant characters. As a result, the average number of character candidates per character was reduced to about 41 candidates, and 94.3% of 1032 slant characters were extracted correctly.
{"title":"Extraction of slant character candidates from maps using circular templates","authors":"O. Shiku, A. Nakamura, Masanori Anegawa, Hideaki Takahira, H. Kuroda","doi":"10.1109/ICDAR.1995.602055","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602055","url":null,"abstract":"The paper proposes a method for extracting slant characters from complicated background figures efficiently and rapidly. In this method, slant character candidates are extracted using the black pixel density features, that is, matching rate of two different sized circular templates, which are inscribing and circumscribing a target character, with an original image. In order to estimate performance of the proposed method, the method was applied to 41 topographic map images (512/spl times/512 pixels) involving 1032 slant characters. As a result, the average number of character candidates per character was reduced to about 41 candidates, and 94.3% of 1032 slant characters were extracted correctly.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"2013 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":"127423358","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.1995.601967
Y. H. Liu-Gong, B. Dubuisson, H. Pham
This paper introduces a new method for transforming the images of a document into its layout structure by the use of an analysis system and several models. The analysis system is independent of the document, and can recognize various documents with the help of some generic models. The definition of a model is based on a document's generic layout structure. The models contain rules necessary for identifying layout structure components.
{"title":"A general analysis system for document's layout structure recognition","authors":"Y. H. Liu-Gong, B. Dubuisson, H. Pham","doi":"10.1109/ICDAR.1995.601967","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601967","url":null,"abstract":"This paper introduces a new method for transforming the images of a document into its layout structure by the use of an analysis system and several models. The analysis system is independent of the document, and can recognize various documents with the help of some generic models. The definition of a model is based on a document's generic layout structure. The models contain rules necessary for identifying layout structure components.","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":"124381619","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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