Pub Date : 1995-08-14DOI: 10.1109/ICDAR.1995.602066
Francis Y. L. Chin, Francis Wu
Magnetic Ink Character Recognition (MICR) technology has widely been used for processing bank checks. Since the MICR character set is a special type font, and the ink is also readable by human being, optical approach can also be used. This report will describe the design of a low-cost, but highly accurate, microprocessor-based optical character recognition (OCR) check reader. The performance of our OCR reader is affected by a number of factors, mainly the noise generated by the lens system and the colour image at the check background. In this paper we describe how our software solution can alleviate these problems. As speed is another concern, special attention is paid to the design of recognition algorithm, such as the avoidance of floating point arithmetics, hardware limitations, etc.
{"title":"A microprocessor-based optical character recognition check reader","authors":"Francis Y. L. Chin, Francis Wu","doi":"10.1109/ICDAR.1995.602066","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602066","url":null,"abstract":"Magnetic Ink Character Recognition (MICR) technology has widely been used for processing bank checks. Since the MICR character set is a special type font, and the ink is also readable by human being, optical approach can also be used. This report will describe the design of a low-cost, but highly accurate, microprocessor-based optical character recognition (OCR) check reader. The performance of our OCR reader is affected by a number of factors, mainly the noise generated by the lens system and the colour image at the check background. In this paper we describe how our software solution can alleviate these problems. As speed is another concern, special attention is paid to the design of recognition algorithm, such as the avoidance of floating point arithmetics, hardware limitations, etc.","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":"121754232","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.1995.601982
Wen Gao, S. Dong, Xilin Chen
Chinese seal imprint verification by computer is very difficult, but is much needed by the application. An improved method for seal imprint verification based on stroke edge matching combined with image difference analysis is proposed. Experimental results show that the proposed approach is excellent in consistency, reliability and adaptability and is feasible for practical applications.
{"title":"A system for automatic Chinese seal imprint verification","authors":"Wen Gao, S. Dong, Xilin Chen","doi":"10.1109/ICDAR.1995.601982","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601982","url":null,"abstract":"Chinese seal imprint verification by computer is very difficult, but is much needed by the application. An improved method for seal imprint verification based on stroke edge matching combined with image difference analysis is proposed. Experimental results show that the proposed approach is excellent in consistency, reliability and adaptability and is feasible for practical applications.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"53 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":"121894866","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.1995.598986
M. Röösli, G. Monagan
We present a vectorization system to generate vector data which corresponds to the line structures of a raster image. The vector data consists of the primitives: "straight lane segment" and "circular arc". The vectorization system measures the quality of each primitive generated. Thus, the vectorization does not only produce high quality vector data, it also gives a precise description of the quality of the data generated. This is crucial if the requirements set by industrial applications are to be met. In order not to lose the quality of the vector data while constructing primitives into line objects, geometric constraints are incorporated already at the vectorization level: constraints like requiring segments to be parallel or perpendicular, circular arcs to be concentric, or tangents of the primitives to be equal at their connection point. After the constraints have been satisfied the resulting primitives still fulfil the quality requirements as before the constraints were imposed. The possibility to refit the generated vector data under adapted constraints allows for an efficient interactive postprocessing of the data.
{"title":"A high quality vectorization combining local quality measures and global constraints","authors":"M. Röösli, G. Monagan","doi":"10.1109/ICDAR.1995.598986","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598986","url":null,"abstract":"We present a vectorization system to generate vector data which corresponds to the line structures of a raster image. The vector data consists of the primitives: \"straight lane segment\" and \"circular arc\". The vectorization system measures the quality of each primitive generated. Thus, the vectorization does not only produce high quality vector data, it also gives a precise description of the quality of the data generated. This is crucial if the requirements set by industrial applications are to be met. In order not to lose the quality of the vector data while constructing primitives into line objects, geometric constraints are incorporated already at the vectorization level: constraints like requiring segments to be parallel or perpendicular, circular arcs to be concentric, or tangents of the primitives to be equal at their connection point. After the constraints have been satisfied the resulting primitives still fulfil the quality requirements as before the constraints were imposed. The possibility to refit the generated vector data under adapted constraints allows for an efficient interactive postprocessing of the data.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"435 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":"126104624","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.1995.599030
Cheng-Lin Liu, Ru-Wei Dai, Ying-Jian Liu
To solve the problem of writer identification (WI) with indeterminate classes (writers) and objects (characters), it is a good way to extract individual features with clear physical meanings and small dynamic ranges. In this paper, a new method named Moment-Based Feature Method to identify Chinese writers is presented in which normalized individual features are derived from geometric moments of character images. The extracted features are invariant under translation, scaling, and stroke-width. They are explicitly corresponding to human perception of shape and distribute their values in small dynamic ranges. Experiments of writer recognition and verification are implemented to demonstrate the efficiency of this method and promising results have been achieved.
{"title":"Extracting individual features from moments for Chinese writer identification","authors":"Cheng-Lin Liu, Ru-Wei Dai, Ying-Jian Liu","doi":"10.1109/ICDAR.1995.599030","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599030","url":null,"abstract":"To solve the problem of writer identification (WI) with indeterminate classes (writers) and objects (characters), it is a good way to extract individual features with clear physical meanings and small dynamic ranges. In this paper, a new method named Moment-Based Feature Method to identify Chinese writers is presented in which normalized individual features are derived from geometric moments of character images. The extracted features are invariant under translation, scaling, and stroke-width. They are explicitly corresponding to human perception of shape and distribute their values in small dynamic ranges. Experiments of writer recognition and verification are implemented to demonstrate the efficiency of this method and promising results have been achieved.","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":"129411856","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.1995.602082
C. Privitera, R. Plamondon
This paper presents a segmentation method that partly mimics the cognitive-behavioral process used by human subjects to recover motor-temporal information from the image of a handwritten word. The approach does not exploit any thinning procedure, but rather a different typology of information is manipulated concerning the curvature of the word contour. Starting from the maximum curvature points roughly corresponding to the beginning of a stroke, the algorithm scans the word, following the natural course of the line and attempts to repeat the same movement as executed by the writer during the generation of the word. At each maximum curvature point, the line is segmented and reconstructed by a smooth interpolation of the most interior points belonging to the line just covered. At the end of the scanning process, a temporal sequence of motor strokes is obtained which plausibly composes the original intended movement.
{"title":"A system for scanning and segmenting cursively handwritten words into basic strokes","authors":"C. Privitera, R. Plamondon","doi":"10.1109/ICDAR.1995.602082","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602082","url":null,"abstract":"This paper presents a segmentation method that partly mimics the cognitive-behavioral process used by human subjects to recover motor-temporal information from the image of a handwritten word. The approach does not exploit any thinning procedure, but rather a different typology of information is manipulated concerning the curvature of the word contour. Starting from the maximum curvature points roughly corresponding to the beginning of a stroke, the algorithm scans the word, following the natural course of the line and attempts to repeat the same movement as executed by the writer during the generation of the word. At each maximum curvature point, the line is segmented and reconstructed by a smooth interpolation of the most interior points belonging to the line just covered. At the end of the scanning process, a temporal sequence of motor strokes is obtained which plausibly composes the original intended movement.","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":"128491004","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.1995.602096
S. Baumann
This paper describes a simplified attributed programmed graph grammar to represent and process a-priori knowledge about common music notation. The presented approach serves as a high-level recognition stage and is interlocked to previous low-level recognition phases in our entire optical music recognition system (DOREMIDI++). The implemented grammar rules and control diagrams describe a declarative knowledge base to drive a transformation algorithm. This transformation converts the results of symbol recognition stages to a symbolic representation of the musical score.
{"title":"A simplified attributed graph grammar for high-level music recognition","authors":"S. Baumann","doi":"10.1109/ICDAR.1995.602096","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602096","url":null,"abstract":"This paper describes a simplified attributed programmed graph grammar to represent and process a-priori knowledge about common music notation. The presented approach serves as a high-level recognition stage and is interlocked to previous low-level recognition phases in our entire optical music recognition system (DOREMIDI++). The implemented grammar rules and control diagrams describe a declarative knowledge base to drive a transformation algorithm. This transformation converts the results of symbol recognition stages to a symbolic representation of the musical score.","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":"129835090","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.1995.602126
Su S. Chen, R. Haralick, I. T. Phillips
This paper describes an algorithm to estimate the text skew angle in a document image. The algorithm utilizes the recursive morphological transforms and yields accurate estimates of text skew angles on a large document image data set. The algorithm computes the optimal parameter settings on the fly without any human interaction. In this automatic mode, experimental results indicate that the algorithm generates estimated text skew angles within 0.5/spl deg/ of the true text skew angles with a probability of 99%. To process a 300 dpi document image, the algorithm takes 10 seconds on SUN Sparc 10 machines.
{"title":"Automatic text skew estimation in document images","authors":"Su S. Chen, R. Haralick, I. T. Phillips","doi":"10.1109/ICDAR.1995.602126","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602126","url":null,"abstract":"This paper describes an algorithm to estimate the text skew angle in a document image. The algorithm utilizes the recursive morphological transforms and yields accurate estimates of text skew angles on a large document image data set. The algorithm computes the optimal parameter settings on the fly without any human interaction. In this automatic mode, experimental results indicate that the algorithm generates estimated text skew angles within 0.5/spl deg/ of the true text skew angles with a probability of 99%. To process a 300 dpi document image, the algorithm takes 10 seconds on SUN Sparc 10 machines.","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":"128912150","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.1995.599026
Ann Grbavec, D. Blostein
This paper investigates graph rewriting as a tool for high-level recognition of two-dimensional mathematical notation. "High-level recognition" is the process of determining the meaning of a diagram from the output of a symbol recognizer. Characteristic problems of high-level mathematics recognition include: determining the groupings of symbols into recursive subexpressions and resolving ambiguities that depend upon global context. Our graph-rewriting approach uses knowledge of the notational conventions of mathematics, such as operator precedence and operator range, more effectively than syntactic or previous structural methods. Graph rewriting offers a flexible formalism with a strong theoretical foundation for manipulating two-dimensional patterns. It has been shown to be a useful technique for high-level recognition of circuit diagrams and musical scores. By demonstrating a graph-rewriting strategy for mathematics recognition, this paper provides further evidence for graph rewriting as a general tool for diagram recognition, and identifies some of the issues that must be considered as this potential is explored.
{"title":"Mathematics recognition using graph rewriting","authors":"Ann Grbavec, D. Blostein","doi":"10.1109/ICDAR.1995.599026","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599026","url":null,"abstract":"This paper investigates graph rewriting as a tool for high-level recognition of two-dimensional mathematical notation. \"High-level recognition\" is the process of determining the meaning of a diagram from the output of a symbol recognizer. Characteristic problems of high-level mathematics recognition include: determining the groupings of symbols into recursive subexpressions and resolving ambiguities that depend upon global context. Our graph-rewriting approach uses knowledge of the notational conventions of mathematics, such as operator precedence and operator range, more effectively than syntactic or previous structural methods. Graph rewriting offers a flexible formalism with a strong theoretical foundation for manipulating two-dimensional patterns. It has been shown to be a useful technique for high-level recognition of circuit diagrams and musical scores. By demonstrating a graph-rewriting strategy for mathematics recognition, this paper provides further evidence for graph rewriting as a general tool for diagram recognition, and identifies some of the issues that must be considered as this potential is explored.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"32 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":"116510208","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.1995.598966
Tyne Liang, Suh-Yin Lee, Wei-Pang Yang
In the application of the superimposed coding method to character-based Chinese text retrieval we find two kinds of false hits for a multi-syllabic (multicharacter) query. The first type is a random false hit (RFH) which is due to accidental setting of bits by irrelevant characters in a document signature. The other type is an adjacency false hit (AFH) which is due to the loss of character sequence information in signature creation. Since many query terms are proper nouns and Chinese names which often contain three characters (tri-syllabic), we derive a formula to estimate the RFH for trisyllabic queries. As for the AFH which cannot be reduced by single character (monogram) hashing method, a method which hashes consecutive character pairs (bigram) is designed to reduce both the AFH and the RFH. We find that there exists an optimal weight assignment for a minimal false hit rate in a combined scheme which encodes both monogram and bigram keys in document signatures.
{"title":"False hits of tri-syllabic queries in a Chinese signature file","authors":"Tyne Liang, Suh-Yin Lee, Wei-Pang Yang","doi":"10.1109/ICDAR.1995.598966","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598966","url":null,"abstract":"In the application of the superimposed coding method to character-based Chinese text retrieval we find two kinds of false hits for a multi-syllabic (multicharacter) query. The first type is a random false hit (RFH) which is due to accidental setting of bits by irrelevant characters in a document signature. The other type is an adjacency false hit (AFH) which is due to the loss of character sequence information in signature creation. Since many query terms are proper nouns and Chinese names which often contain three characters (tri-syllabic), we derive a formula to estimate the RFH for trisyllabic queries. As for the AFH which cannot be reduced by single character (monogram) hashing method, a method which hashes consecutive character pairs (bigram) is designed to reduce both the AFH and the RFH. We find that there exists an optimal weight assignment for a minimal false hit rate in a combined scheme which encodes both monogram and bigram keys in document signatures.","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":"125858557","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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