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to the signature verification process; an additional alignment stage before the actual nonlinear correlation is obsolete.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to the signature verification process; an additional alignment stage before the actual nonlinear correlation is obsolete.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and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.1995.602018
P. Stubberud, J. Kanai, V. Kalluri
To improve the performance of an optical character recognition (OCR) system, an adaptive technique that restores touching or broken character images is proposed. By using the output from an OCR system and a distorted text image, this technique trains an adaptive restoration filter and then applies the filter to the distorted text image that the OCR system could not recognize. To demonstrate the performance of this technique, two synthesized images containing only touching characters and two synthesized images containing only broken characters were processed. The results show that this technique can improve both pixel and character accuracy of text images containing touching or broken characters.
{"title":"Adaptive image restoration of text images that contain touching or broken characters","authors":"P. Stubberud, J. Kanai, V. Kalluri","doi":"10.1109/ICDAR.1995.602018","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602018","url":null,"abstract":"To improve the performance of an optical character recognition (OCR) system, an adaptive technique that restores touching or broken character images is proposed. By using the output from an OCR system and a distorted text image, this technique trains an adaptive restoration filter and then applies the filter to the distorted text image that the OCR system could not recognize. To demonstrate the performance of this technique, two synthesized images containing only touching characters and two synthesized images containing only broken characters were processed. The results show that this technique can improve both pixel and character accuracy of text images containing touching or broken characters.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"20 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":"122871360","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.1995.602047
S. Tsuruoka, N. Watanabe, N. Minamide, F. Kimura, Y. Miyake, M. Shridhar
The authors have researched two-letter state name (state name abbreviation) recognition and full state name recognition. According to this research, they think that the accuracy of the character segmentation is essential to recognize the word correctly, and it depends on the normalization of the word image. The normalization includes smoothing, underline removal, spurious blob removal, slant and base line correction etc. They present a new base line correction algorithm for the off-line handwritten words, which include cursive (continuous or running) words and hand-printed words. It uses background region analysis with the lower convex hull which is background area closed for three directions (upper, right, left), and the upper and bottom profiles of the merged convex hull. The authors show that the new method of base line correction is very powerful for most word images for city names of the USPS mail address database. The resulting image is useful for the holistic approach, and it's effective even when the image includes parts under the base line, for example, "f", "g", "j", or a very large character.
{"title":"Base line correction for handwritten word recognition","authors":"S. Tsuruoka, N. Watanabe, N. Minamide, F. Kimura, Y. Miyake, M. Shridhar","doi":"10.1109/ICDAR.1995.602047","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602047","url":null,"abstract":"The authors have researched two-letter state name (state name abbreviation) recognition and full state name recognition. According to this research, they think that the accuracy of the character segmentation is essential to recognize the word correctly, and it depends on the normalization of the word image. The normalization includes smoothing, underline removal, spurious blob removal, slant and base line correction etc. They present a new base line correction algorithm for the off-line handwritten words, which include cursive (continuous or running) words and hand-printed words. It uses background region analysis with the lower convex hull which is background area closed for three directions (upper, right, left), and the upper and bottom profiles of the merged convex hull. The authors show that the new method of base line correction is very powerful for most word images for city names of the USPS mail address database. The resulting image is useful for the holistic approach, and it's effective even when the image includes parts under the base line, for example, \"f\", \"g\", \"j\", or a very large character.","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":"127916058","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.1995.601955
G. P. Zarri
The "Narrative Knowledge Representation Language" (NKRL) has been expressly created to provide a standard, language-independent description of the semantic content (the "meaning") of complex, natural language "narrative" documents (news stories, telex reports, corporate documentation, regulations and normative texts, intelligence messages, etc.). After having introduced the four components (specialised sublanguages) of NKRL, we will give some examples of the possibilities offered by this language with respect to the optimal coding of the meaning of textual documents.
{"title":"The \"Narrative Knowledge Representation Language\", a knowledge-based approach for representing the \"meaning\" of textual documents","authors":"G. P. Zarri","doi":"10.1109/ICDAR.1995.601955","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601955","url":null,"abstract":"The \"Narrative Knowledge Representation Language\" (NKRL) has been expressly created to provide a standard, language-independent description of the semantic content (the \"meaning\") of complex, natural language \"narrative\" documents (news stories, telex reports, corporate documentation, regulations and normative texts, intelligence messages, etc.). After having introduced the four components (specialised sublanguages) of NKRL, we will give some examples of the possibilities offered by this language with respect to the optimal coding of the meaning of textual documents.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"22 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":"127961258","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.1995.598992
Tao Hong, S. Lam, J. Hull, S. Srihari
The nearest neighbor (NN) approach is a powerful nonparametric technique for pattern classification tasks. In this paper, algorithms for prototype reduction, hierarchical prototype organization and fast NN search are described. To remove redundant category prototypes and to avoid redundant comparisons, the algorithms explain geometrical information of a given prototype set which is represented approximately by computing k-nearest/farthest neighbors of each prototype. The performance of a NN classifier using those algorithms for Japanese character recognition is reported.
{"title":"The design of a nearest-neighbor classifier and its use for Japanese character recognition","authors":"Tao Hong, S. Lam, J. Hull, S. Srihari","doi":"10.1109/ICDAR.1995.598992","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598992","url":null,"abstract":"The nearest neighbor (NN) approach is a powerful nonparametric technique for pattern classification tasks. In this paper, algorithms for prototype reduction, hierarchical prototype organization and fast NN search are described. To remove redundant category prototypes and to avoid redundant comparisons, the algorithms explain geometrical information of a given prototype set which is represented approximately by computing k-nearest/farthest neighbors of each prototype. The performance of a NN classifier using those algorithms for Japanese character recognition is reported.","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":"128979329","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.1995.598963
Yu Zhong, K. Karu, Anil K. Jain
There is a substantial interest in retrieving images from a large database using the textual information contained in the images. An algorithm which will automatically locate the textual regions in the input image will facilitate this task; the optical character recognizer can then be applied to only those regions of the image which contain text. We present a method for automatically locating text in complex color images. The algorithm first finds the approximate locations of text lines using horizontal spatial variance, and then extracts text components in these boxes using color segmentation. The proposed method has been used to locate text in compact disc (CD) and book cover images, as well as in the images of traffic scenes captured by a video camera. Initial results are encouraging and suggest that these algorithms can be used in image retrieval applications.
{"title":"Locating text in complex color images","authors":"Yu Zhong, K. Karu, Anil K. Jain","doi":"10.1109/ICDAR.1995.598963","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598963","url":null,"abstract":"There is a substantial interest in retrieving images from a large database using the textual information contained in the images. An algorithm which will automatically locate the textual regions in the input image will facilitate this task; the optical character recognizer can then be applied to only those regions of the image which contain text. We present a method for automatically locating text in complex color images. The algorithm first finds the approximate locations of text lines using horizontal spatial variance, and then extracts text components in these boxes using color segmentation. The proposed method has been used to locate text in compact disc (CD) and book cover images, as well as in the images of traffic scenes captured by a video camera. Initial results are encouraging and suggest that these algorithms can be used in image retrieval applications.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"45 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":"128681632","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.1995.602020
Yuhong Yu, A. Samal, S. Seth
We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.
{"title":"A system for recognizing a large class of engineering drawings","authors":"Yuhong Yu, A. Samal, S. Seth","doi":"10.1109/ICDAR.1995.602020","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602020","url":null,"abstract":"We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"433 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":"116007514","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.1995.601973
Kuo-Chin Fan, J. Lu, Jiing-Yuh Wang
Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the novel method is demonstrated through experimenting various kinds of forms. Experimental results reveal the feasibility of the novel method.
{"title":"A feature point clustering approach to the segmentation of form documents","authors":"Kuo-Chin Fan, J. Lu, Jiing-Yuh Wang","doi":"10.1109/ICDAR.1995.601973","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601973","url":null,"abstract":"Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the novel method is demonstrated through experimenting various kinds of forms. Experimental results reveal the feasibility of the novel method.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115353313","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}
The Chinese archive document possesses special geometrical and logical properties due to its construction based upon rectangular field which contain either title strings or data strings related to some other titles. In this paper, we propose a knowledge-based approach to analyze the logical relationship among the fields. After extracting the lines and fields of an archive document image, this procedure can identify fields as the title fields, the sub-title fields (if there exist such tree-structure logical relationship), and the corresponding data fields. This proposed approach enables us to achieve a better performance in information manipulation of archive documents.
{"title":"A knowledge-based approach to Chinese archive document understanding","authors":"Shih-Shien You, Gan-How Chang, Pao-Chung Chang, Bing-Shan Chien","doi":"10.1109/ICDAR.1995.601957","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.601957","url":null,"abstract":"The Chinese archive document possesses special geometrical and logical properties due to its construction based upon rectangular field which contain either title strings or data strings related to some other titles. In this paper, we propose a knowledge-based approach to analyze the logical relationship among the fields. After extracting the lines and fields of an archive document image, this procedure can identify fields as the title fields, the sub-title fields (if there exist such tree-structure logical relationship), and the corresponding data fields. This proposed approach enables us to achieve a better performance in information manipulation of archive documents.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"22 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":"114390578","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.1995.599009
R. E. Marston, M. Kuo
Previous work on the reconstruction of planar-faced objects from 3-view engineering drawings is extended, to include objects having central quadric surfaces with conic-section boundary edges. Multiple solutions are available from the algorithm and pathological situations arising from back-projection are eliminated. The algorithm accepts a wider variety of curved surface objects and imposes fewer restrictions on acceptable input drawings than previous methods.
{"title":"Interpretation of 3-view engineering drawings as central quadric surface mechanical parts","authors":"R. E. Marston, M. Kuo","doi":"10.1109/ICDAR.1995.599009","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599009","url":null,"abstract":"Previous work on the reconstruction of planar-faced objects from 3-view engineering drawings is extended, to include objects having central quadric surfaces with conic-section boundary edges. Multiple solutions are available from the algorithm and pathological situations arising from back-projection are eliminated. The algorithm accepts a wider variety of curved surface objects and imposes fewer restrictions on acceptable input drawings than previous methods.","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":"125813704","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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