Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.602053
L. Eikvil, K. Aas, H. Koren
The process of converting an analog map into structured digitized information requires several different operations, which are all time-consuming when performed manually. Strictly automatic processing is not always a possible solution, and an interactive approach can then be an alternative. The paper describes a tool for map conversion, focusing on the functionality for extraction of line structures. An interactive approach is used as it gives the user an opportunity to survey the process, and utilize human knowledge. The methods are based on contour following, extracting centre points needed for accurate vector representation of the line during tracing.
{"title":"Tools for interactive map conversion and vectorization","authors":"L. Eikvil, K. Aas, H. Koren","doi":"10.1109/ICDAR.1995.602053","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602053","url":null,"abstract":"The process of converting an analog map into structured digitized information requires several different operations, which are all time-consuming when performed manually. Strictly automatic processing is not always a possible solution, and an interactive approach can then be an alternative. The paper describes a tool for map conversion, focusing on the functionality for extraction of line structures. An interactive approach is used as it gives the user an opportunity to survey the process, and utilize human knowledge. The methods are based on contour following, extracting centre points needed for accurate vector representation of the line during tracing.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"90 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":"116019805","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.1995.598962
Y. Gao, J. J. Lim, A. D. Narasimhalu
The thesaurus is widely used in information indexing and retrieval for vocabulary control and concept search. Conceptual relationships are usually reciprocal and many-to-many, and can hardly be described precisely. To comply with the imprecise nature of the thesaurus, we have proposed and developed a fuzzy multilinkage thesaurus builder. The builder maintains a fuzzy membership degree for each relationship. The relationships are extensible and have an inheritance capability. The applications of the fuzzy multilinkage thesaurus builder to expand the query terms for multimedia information retrieval are presented.
{"title":"Fuzzy multilinkage thesaurus builder in multimedia information systems","authors":"Y. Gao, J. J. Lim, A. D. Narasimhalu","doi":"10.1109/ICDAR.1995.598962","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598962","url":null,"abstract":"The thesaurus is widely used in information indexing and retrieval for vocabulary control and concept search. Conceptual relationships are usually reciprocal and many-to-many, and can hardly be described precisely. To comply with the imprecise nature of the thesaurus, we have proposed and developed a fuzzy multilinkage thesaurus builder. The builder maintains a fuzzy membership degree for each relationship. The relationships are extensible and have an inheritance capability. The applications of the fuzzy multilinkage thesaurus builder to expand the query terms for multimedia information retrieval are presented.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"133 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":"123586855","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.1995.602097
Hsi-Jian Lee, Jiumn-Shine Wang
We present a system to segment and recognize texts and mathematical expressions in a document. The system can be divided into six stages: page segmentation and labeling, character segmentation, feature extraction, character recognition, expression formation, and error correction and expression extraction. In expression formation, we build a symbol relation tree for each text line to represent the relationships among the symbols in the text line. Some heuristic rules based on the primitive tokens are used to correct the recognition errors in a text line. We extract all mathematical expressions according to some basic expression forms. Our database consists of 190 symbols in the current stage. The average recognition rate is about 96.16%.
{"title":"Design of a mathematical expression recognition system","authors":"Hsi-Jian Lee, Jiumn-Shine Wang","doi":"10.1109/ICDAR.1995.602097","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602097","url":null,"abstract":"We present a system to segment and recognize texts and mathematical expressions in a document. The system can be divided into six stages: page segmentation and labeling, character segmentation, feature extraction, character recognition, expression formation, and error correction and expression extraction. In expression formation, we build a symbol relation tree for each text line to represent the relationships among the symbols in the text line. Some heuristic rules based on the primitive tokens are used to correct the recognition errors in a text line. We extract all mathematical expressions according to some basic expression forms. Our database consists of 190 symbols in the current stage. The average recognition rate is about 96.16%.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"41 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":"116855487","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.1995.599043
G. Menier, G. Lorette, P. Gentric
This paper introduces and discusses the concept of stable and shared information and its application in a new modeling method based on the selection of features. The model constructed is used for the automatic detection of scriptor-independent information. The selected features are treated as functions in order to allow a continuous interpretation of the script signal. This proposed representation permits the joint interpretation of on-line and off-line information. The paper then goes on to present some experimental results.
{"title":"A new modeling method for on-line handwriting recognition","authors":"G. Menier, G. Lorette, P. Gentric","doi":"10.1109/ICDAR.1995.599043","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599043","url":null,"abstract":"This paper introduces and discusses the concept of stable and shared information and its application in a new modeling method based on the selection of features. The model constructed is used for the automatic detection of scriptor-independent information. The selected features are treated as functions in order to allow a continuous interpretation of the script signal. This proposed representation permits the joint interpretation of on-line and off-line information. The paper then goes on to present some experimental results.","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":"124610677","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.1995.602068
H. Samet, A. Soffer
A system for the acquisition, storage, indexing, and retrieval of map images is presented. The input to this system are raster images of separate map layers and map composites. A legend driven map interpretation system converts layer images from a physical to a logical representation. This logical representation is used to automatically index both the composite and the layer images. Methods for incorporating logical and physical layers as well as composite images into the framework of a relational database management system are described. An example query and a corresponding query processing strategy that uses these indices is presented. The user interface is demonstrated via an example query execution.
{"title":"A map acquisition, storage, indexing, and retrieval system","authors":"H. Samet, A. Soffer","doi":"10.1109/ICDAR.1995.602068","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602068","url":null,"abstract":"A system for the acquisition, storage, indexing, and retrieval of map images is presented. The input to this system are raster images of separate map layers and map composites. A legend driven map interpretation system converts layer images from a physical to a logical representation. This logical representation is used to automatically index both the composite and the layer images. Methods for incorporating logical and physical layers as well as composite images into the framework of a relational database management system are described. An example query and a corresponding query processing strategy that uses these indices is presented. The user interface is demonstrated via an example query execution.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"117 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":"124761546","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.1995.598936
Gyeonghwan Kim, V. Govindaraju
A fast handwritten word recognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each character of a lexicon entry and segment(s) of input word image is used for ranking words in the lexicon. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform for lexicon size of 10. A top choice performance of 96% is achieved on a database of postal words captured at 212 dpi.
{"title":"Handwritten word recognition for real-time applications","authors":"Gyeonghwan Kim, V. Govindaraju","doi":"10.1109/ICDAR.1995.598936","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598936","url":null,"abstract":"A fast handwritten word recognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each character of a lexicon entry and segment(s) of input word image is used for ranking words in the lexicon. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform for lexicon size of 10. A top choice performance of 96% is achieved on a database of postal words captured at 212 dpi.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"44 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":"124799133","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.1995.598946
R. Powalka, N. Sherkat, R. Whitrow
The paper concentrates on the combination of results of multiple recognizers at the word level. Two approaches are presented: word list merging and linear combination. Word list merging requires no knowledge about the individual recognizers. The linear combination is an attempt to exploit the information about characteristics of individual recognizers. This appears more complex than in the case of combination of results at the character level. Recognition of words is influenced by more factors, which can independently affect the recognition process. Characterisation of recognizers, used for word level combination, is more complex and requires more than a simple consideration of recognition success and failure. The concept of handwriting data characterisation is defined. A number of handwriting characteristics are extracted and used to guide the combination process. The choice of characteristics is made in the context of recognition methods used. No attempt at general characterisation of handwriting is made. The relationship between handwriting characteristics and recognition results is observed and used to obtain characteristics of individual recognizers. Results of the two combination methods are reported and compared with another frequently used method for results combination, the Borda count.
{"title":"Recognizer characterisation for combining handwriting recognition results at word level","authors":"R. Powalka, N. Sherkat, R. Whitrow","doi":"10.1109/ICDAR.1995.598946","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598946","url":null,"abstract":"The paper concentrates on the combination of results of multiple recognizers at the word level. Two approaches are presented: word list merging and linear combination. Word list merging requires no knowledge about the individual recognizers. The linear combination is an attempt to exploit the information about characteristics of individual recognizers. This appears more complex than in the case of combination of results at the character level. Recognition of words is influenced by more factors, which can independently affect the recognition process. Characterisation of recognizers, used for word level combination, is more complex and requires more than a simple consideration of recognition success and failure. The concept of handwriting data characterisation is defined. A number of handwriting characteristics are extracted and used to guide the combination process. The choice of characteristics is made in the context of recognition methods used. No attempt at general characterisation of handwriting is made. The relationship between handwriting characteristics and recognition results is observed and used to obtain characteristics of individual recognizers. Results of the two combination methods are reported and compared with another frequently used method for results combination, the Borda count.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"35 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":"125073910","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.1995.598968
Masanori Sugimoto, K. Hori, S. Ohsuga
A document retrieval system for researchers in the field of science and technology is described. The main feature of the system is the visualization of the semantic relations between documents and interactive operation to it. The system has a test database composed of a large number of journal and conference papers. It elicits keywords from each paper by an automatic indexing algorithm and then visualizes the relations between the papers and their keywords in a metric space by a statistical method. We carried out several experiments. Through them we have confirmed that our system is effective because it can assist the users in their query formation and modification while they use it. Our system can also assist the users in their creative research because they can find the relations between the papers and their keywords which they haven't noticed so far. In the experiment on effectiveness of retrieval we have confirmed that our system can realize high recall and precision ratio.
{"title":"A document retrieval system for assisting creative research","authors":"Masanori Sugimoto, K. Hori, S. Ohsuga","doi":"10.1109/ICDAR.1995.598968","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598968","url":null,"abstract":"A document retrieval system for researchers in the field of science and technology is described. The main feature of the system is the visualization of the semantic relations between documents and interactive operation to it. The system has a test database composed of a large number of journal and conference papers. It elicits keywords from each paper by an automatic indexing algorithm and then visualizes the relations between the papers and their keywords in a metric space by a statistical method. We carried out several experiments. Through them we have confirmed that our system is effective because it can assist the users in their query formation and modification while they use it. Our system can also assist the users in their creative research because they can find the relations between the papers and their keywords which they haven't noticed so far. In the experiment on effectiveness of retrieval we have confirmed that our system can realize high recall and precision ratio.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"54 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":"128374655","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.1995.598974
N. Murshed, Flávio Bortolozzi, R. Sabourin
This work proposes a new approach to signature verification. It is inspired by the human learning and the approach adopted by the expert examiner of signatures, in which an a priori knowledge of the class of forgeries is not required in order to perform the verification task. Based on this approach, we present a Fuzzy ARTMAP based system for the elimination of random forgeries. Compared to the conventional systems proposed thus far, the presented system is trained with genuine signatures only. Six experiments have been performed on a data base of 200 signatures taken from five writers (40 signatures/writer). Evaluation of the system was measured using different numbers of training signatures.
{"title":"Off-line signature verification, without a priori knowledge of class /spl omega//sub 2/. A new approach","authors":"N. Murshed, Flávio Bortolozzi, R. Sabourin","doi":"10.1109/ICDAR.1995.598974","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598974","url":null,"abstract":"This work proposes a new approach to signature verification. It is inspired by the human learning and the approach adopted by the expert examiner of signatures, in which an a priori knowledge of the class of forgeries is not required in order to perform the verification task. Based on this approach, we present a Fuzzy ARTMAP based system for the elimination of random forgeries. Compared to the conventional systems proposed thus far, the presented system is trained with genuine signatures only. Six experiments have been performed on a data base of 200 signatures taken from five writers (40 signatures/writer). Evaluation of the system was measured using different numbers of training signatures.","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":"128753150","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.1995.602094
D. Yeung
In this paper, we present a grammar-based approach to the modeling and recognition of temporal sequences. Unlike hidden Markov models which require humans to determine in advance the appropriate model architecture to work on, our approach does not rely on prior knowledge about the topology of the underlying grammars. In particular, a discrete-time recurrent neural network model is proposed to learn separately the dynamics of each embedded subgrammar (or subpattern) class. These subgrammar network models are trained using an unsupervised learning paradigm called auto-associative (or self-supervised) learning. In this pilot study, some issues of this new approach to temporal sequence processing are investigated in the domain of on-line handwriting modeling and recognition. Some possible future research directions are also discussed.
{"title":"A grammatical inference approach to on-line handwriting modeling and recognition: a pilot study","authors":"D. Yeung","doi":"10.1109/ICDAR.1995.602094","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602094","url":null,"abstract":"In this paper, we present a grammar-based approach to the modeling and recognition of temporal sequences. Unlike hidden Markov models which require humans to determine in advance the appropriate model architecture to work on, our approach does not rely on prior knowledge about the topology of the underlying grammars. In particular, a discrete-time recurrent neural network model is proposed to learn separately the dynamics of each embedded subgrammar (or subpattern) class. These subgrammar network models are trained using an unsupervised learning paradigm called auto-associative (or self-supervised) learning. In this pilot study, some issues of this new approach to temporal sequence processing are investigated in the domain of on-line handwriting modeling and recognition. Some possible future research directions are also discussed.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"2 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":"129122509","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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