Pub Date : 1997-08-18DOI: 10.1109/ICDAR.1997.620620
A. Vossepoel, K. Schutte, Carl F. P. Delanghe
An algorithm is presented that allows one to perform skeletonization of large maps with much lower memory requirements than with the straightforward approach. The maps are divided into overlapping tiles, which are skeletonized separately, using a Euclidean distance transform. The amount of overlap is controlled by the maximum expected width of any map component and the maximum size of what is considered as a small component. Next, the skeleton parts are connected again at the middle of the overlap zones. Some examples are given for efficient memory utilization in tiling an A0 size map into a predefined number of tiles or into tiles of a predefined (square) size. The algorithm is also suited for a parallel implementation of skeletonization.
{"title":"Memory efficient skeletonization of utility maps","authors":"A. Vossepoel, K. Schutte, Carl F. P. Delanghe","doi":"10.1109/ICDAR.1997.620620","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620620","url":null,"abstract":"An algorithm is presented that allows one to perform skeletonization of large maps with much lower memory requirements than with the straightforward approach. The maps are divided into overlapping tiles, which are skeletonized separately, using a Euclidean distance transform. The amount of overlap is controlled by the maximum expected width of any map component and the maximum size of what is considered as a small component. Next, the skeleton parts are connected again at the middle of the overlap zones. Some examples are given for efficient memory utilization in tiling an A0 size map into a predefined number of tiles or into tiles of a predefined (square) size. The algorithm is also suited for a parallel implementation of skeletonization.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":" 29","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132041884","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.620663
Eiki Ishidera, D. Nishiwaki, Keiji Yamada
We describe a new handwritten address recognition method which can correct the errors occurring in line extraction, character segmentation, and character recognition as a possible means of avoiding the error accumulation which occurs during the recognition sequence in conventional methods. We formulate the address recognition method as a minimum cost search problem. We define the character recognition cost which estimates the reliability of the character recognition result, the arrangement cost which estimates the plausibility of the character string's spatial arrangement, and the word knowledge cost which estimates the plausibility of the linguistic conditions. By using a combination of these costs, the proposed method can recognize an address which has not been extracted as a single line from input images by a conventional method. The efficiency of the proposed method is evaluated through an experiment using 600 Japanese mail images. An address recognition rate of 79.38% was obtained.
{"title":"Unconstrained Japanese address recognition using a combination of spatial information and word knowledge","authors":"Eiki Ishidera, D. Nishiwaki, Keiji Yamada","doi":"10.1109/ICDAR.1997.620663","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620663","url":null,"abstract":"We describe a new handwritten address recognition method which can correct the errors occurring in line extraction, character segmentation, and character recognition as a possible means of avoiding the error accumulation which occurs during the recognition sequence in conventional methods. We formulate the address recognition method as a minimum cost search problem. We define the character recognition cost which estimates the reliability of the character recognition result, the arrangement cost which estimates the plausibility of the character string's spatial arrangement, and the word knowledge cost which estimates the plausibility of the linguistic conditions. By using a combination of these costs, the proposed method can recognize an address which has not been extracted as a single line from input images by a conventional method. The efficiency of the proposed method is evaluated through an experiment using 600 Japanese mail images. An address recognition rate of 79.38% was obtained.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133426938","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.619874
M. Nakagawa, Takao Higashiyama, Yukiko Yamanaka, S. Sawada, Levan Higashigawa, K. Akiyama
The paper presents a database of on-line handwritten character patterns sampled in a sequence of sentences without any instructions. The sentences according to which character patterns are collected have been picked up from newspaper to include 1227 frequently appearing character categories with the result that they are composed of about 10000 characters and include 1537 JIS 1st level character categories. The rest of the JIS 1st level 1808 categories have been added at the end of the above text and written one by one. The total text has been commonly employed for collecting script patterns from a number of people. Patterns offered were inspected and omissions and wrong patterns were rewritten. The authors collected data from 80 people and made the 12000/spl times/80 patterns available from February 1996. More patterns are being collected. The paper describes the characteristics of this database as well as several tools to collect patterns.
{"title":"On-line handwritten character pattern database sampled in a sequence of sentences without any writing instructions","authors":"M. Nakagawa, Takao Higashiyama, Yukiko Yamanaka, S. Sawada, Levan Higashigawa, K. Akiyama","doi":"10.1109/ICDAR.1997.619874","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.619874","url":null,"abstract":"The paper presents a database of on-line handwritten character patterns sampled in a sequence of sentences without any instructions. The sentences according to which character patterns are collected have been picked up from newspaper to include 1227 frequently appearing character categories with the result that they are composed of about 10000 characters and include 1537 JIS 1st level character categories. The rest of the JIS 1st level 1808 categories have been added at the end of the above text and written one by one. The total text has been commonly employed for collecting script patterns from a number of people. Patterns offered were inspected and omissions and wrong patterns were rewritten. The authors collected data from 80 people and made the 12000/spl times/80 patterns available from February 1996. More patterns are being collected. The paper describes the characteristics of this database as well as several tools to collect patterns.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133875351","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.619863
D. Doermann, Huiping Li, O. Kia
We propose and implement a method for detecting duplicate documents in very large image databases. The method is based on a robust "signature" extracted from each document image which is used to index into a table of previously processed documents. The approach has a number of advantages over OCR or other recognition based methods, including speed and robustness to imaging distortions. To justify the approach and test the scalability, we have developed a simulator which allows us to change parameters of the system and examine performance for millions of document signatures. A complete system is implemented and tested on a test collection of technical articles and memos.
{"title":"The detection of duplicates in document image databases","authors":"D. Doermann, Huiping Li, O. Kia","doi":"10.1109/ICDAR.1997.619863","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.619863","url":null,"abstract":"We propose and implement a method for detecting duplicate documents in very large image databases. The method is based on a robust \"signature\" extracted from each document image which is used to index into a table of previously processed documents. The approach has a number of advantages over OCR or other recognition based methods, including speed and robustness to imaging distortions. To justify the approach and test the scalability, we have developed a simulator which allows us to change parameters of the system and examine performance for millions of document signatures. A complete system is implemented and tested on a test collection of technical articles and memos.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116323500","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.620581
Yi-Hong Tseng, Chi-Chang Kuo, Hsi-Jian Lee
We present two techniques for speeding up character recognition. Our character recognition system, including the candidate cluster selection and detail matching modules, is implemented using two statistical features: crossing counts and contour direction counts. In the training stage, we divide characters into different clusters. To keep a very high recognition rate, the candidate cluster selection module selects the top 60 clusters with minimal distances from among 300 predefined clusters. To further speed up the recognition speed, we use a modified branch and bound algorithm in the detail matching module. In the automatic document reading system, characters and punctuation marks are first extracted from printed document images and sorted according to their positions and the document orientation. The system then recognizes all printed Chinese characters between pairs of punctuation marks. The results are then spoken aloud by a speech synthesis system.
{"title":"Speeding-up Chinese character recognition in an automatic document reading system","authors":"Yi-Hong Tseng, Chi-Chang Kuo, Hsi-Jian Lee","doi":"10.1109/ICDAR.1997.620581","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620581","url":null,"abstract":"We present two techniques for speeding up character recognition. Our character recognition system, including the candidate cluster selection and detail matching modules, is implemented using two statistical features: crossing counts and contour direction counts. In the training stage, we divide characters into different clusters. To keep a very high recognition rate, the candidate cluster selection module selects the top 60 clusters with minimal distances from among 300 predefined clusters. To further speed up the recognition speed, we use a modified branch and bound algorithm in the detail matching module. In the automatic document reading system, characters and punctuation marks are first extracted from printed document images and sorted according to their positions and the document orientation. The system then recognizes all printed Chinese characters between pairs of punctuation marks. The results are then spoken aloud by a speech synthesis system.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125153129","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.620548
T. Yamauchi, Y. Itamoto, J. Tsukumo
Character recognition using multi-template methods is promising. Higher classification performance can be achieved according to an increase in the number of templates. However, classification performance is saturated because there is classifiability loss in feature extraction. The paper proposes a new multi-template method which learns training patterns with character shape information assigned by the authors. This method uses contour feature and direction feature, and includes a character shape consistency test applied to the conventional multi-template methods. The paper presents experimental results obtained from handprinted numerals. On the ETL-6 database classification experiment the classification rate was 99.19% and the substitution rate was 0.03%. A higher classification rate could be achieved.
{"title":"Shape based learning for a multi-template method, and its application to handprinted numeral recognition","authors":"T. Yamauchi, Y. Itamoto, J. Tsukumo","doi":"10.1109/ICDAR.1997.620548","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620548","url":null,"abstract":"Character recognition using multi-template methods is promising. Higher classification performance can be achieved according to an increase in the number of templates. However, classification performance is saturated because there is classifiability loss in feature extraction. The paper proposes a new multi-template method which learns training patterns with character shape information assigned by the authors. This method uses contour feature and direction feature, and includes a character shape consistency test applied to the conventional multi-template methods. The paper presents experimental results obtained from handprinted numerals. On the ETL-6 database classification experiment the classification rate was 99.19% and the substitution rate was 0.03%. A higher classification rate could be achieved.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128343694","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.620570
Chiu L. Yu, C. Suen, Y. Tang
This paper describes a Chinese cheque processing system currently under development at the Centre for Pattern Recognition and Machine Intelligence (CENPARMI). The information on Chinese bank cheques is not the same as that on alphanumeric bank cheques. The legal amount in a Chinese bank cheque is the Chinese character text associated with each currency unit. This paper discusses a technique using each currency unit as a key word to locate/extract the legal amount in bank cheques. In the analysis and recognition process, the system tries to locate the smallest currency units in the image and identifies it first. Then, the system tries to locate the image strings associated with each currency unit. Each image string is separated and recognized. Next, a set of rules and context are applied to recognize the characters. In order to choose the correct one, the recognized character string is accepted only if it satisfies all the conditions governed by rules.
{"title":"Location and recognition of legal amounts on Chinese bank cheques","authors":"Chiu L. Yu, C. Suen, Y. Tang","doi":"10.1109/ICDAR.1997.620570","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620570","url":null,"abstract":"This paper describes a Chinese cheque processing system currently under development at the Centre for Pattern Recognition and Machine Intelligence (CENPARMI). The information on Chinese bank cheques is not the same as that on alphanumeric bank cheques. The legal amount in a Chinese bank cheque is the Chinese character text associated with each currency unit. This paper discusses a technique using each currency unit as a key word to locate/extract the legal amount in bank cheques. In the analysis and recognition process, the system tries to locate the smallest currency units in the image and identifies it first. Then, the system tries to locate the image strings associated with each currency unit. Each image string is separated and recognized. Next, a set of rules and context are applied to recognize the characters. In order to choose the correct one, the recognized character string is accepted only if it satisfies all the conditions governed by rules.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128675433","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.619809
Anil K. Jain, B. Yu
Transforming a paper document to its electronic version in a form suitable for efficient storage, retrieval and interpretation continues to be a challenging problem. An efficient document model is necessary to solve this problem. Document modeling involves techniques of thresholding, skew detection, geometric layout analysis and logical layout analysis. The derived model can then be used in document storage and retrieval. We use the traditional bottom-up approach based on the connected component extraction to efficiently implement page segmentation and region identification. A new document model which preserves top-down generation information is proposed based on which a document is logically represented for interactive editing, storage, retrieval, transfer and logical analysis.
{"title":"Page segmentation using document model","authors":"Anil K. Jain, B. Yu","doi":"10.1109/ICDAR.1997.619809","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.619809","url":null,"abstract":"Transforming a paper document to its electronic version in a form suitable for efficient storage, retrieval and interpretation continues to be a challenging problem. An efficient document model is necessary to solve this problem. Document modeling involves techniques of thresholding, skew detection, geometric layout analysis and logical layout analysis. The derived model can then be used in document storage and retrieval. We use the traditional bottom-up approach based on the connected component extraction to efficiently implement page segmentation and region identification. A new document model which preserves top-down generation information is proposed based on which a document is logically represented for interactive editing, storage, retrieval, transfer and logical analysis.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131097613","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.620572
A. Amin
Machine simulation of human reading has been the subject of intensive research for almost three decades. A large number of research papers and reports have already been published on Latin, Chinese and Japanese characters. However, little work has been conducted on the automatic recognition of Arabic characters because of the complexity of printed and handwritten text, and this problem is still an open research field. The main objective of this paper is to present the state of Arabic character recognition research throughout the last two decades.
{"title":"Off line Arabic character recognition: a survey","authors":"A. Amin","doi":"10.1109/ICDAR.1997.620572","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.620572","url":null,"abstract":"Machine simulation of human reading has been the subject of intensive research for almost three decades. A large number of research papers and reports have already been published on Latin, Chinese and Japanese characters. However, little work has been conducted on the automatic recognition of Arabic characters because of the complexity of printed and handwritten text, and this problem is still an open research field. The main objective of this paper is to present the state of Arabic character recognition research throughout the last two decades.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130272094","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 : 1997-08-18DOI: 10.1109/ICDAR.1997.619853
Christiane Schmidt, K. Kraiss
The paper presents a novel method of on-line signature verification that analyzes both the shape of the signature and dynamics of the writing process. This approach automatically determines characteristic features of the written image and combines these shape features with features from the writing dynamics. For establishing a writing characteristic template for one signer the signature is separated into characteristic segments. The segmentation algorithm extracts writing points which would give a forgery the appearance of the original. For these significant points local extreme values, which identify writing segments, are calculated. Subsequently, dynamic features are computed for the segments. The developed system needs three signatures of one person for the establishment of a personalized template. A database has been collected with 544 signatures of 27 signers for evaluation. The developed system achieved a correct acceptance rate of 78% and a correct rejection rate of 100%.
{"title":"Establishment of personalized templates for automatic signature verification","authors":"Christiane Schmidt, K. Kraiss","doi":"10.1109/ICDAR.1997.619853","DOIUrl":"https://doi.org/10.1109/ICDAR.1997.619853","url":null,"abstract":"The paper presents a novel method of on-line signature verification that analyzes both the shape of the signature and dynamics of the writing process. This approach automatically determines characteristic features of the written image and combines these shape features with features from the writing dynamics. For establishing a writing characteristic template for one signer the signature is separated into characteristic segments. The segmentation algorithm extracts writing points which would give a forgery the appearance of the original. For these significant points local extreme values, which identify writing segments, are calculated. Subsequently, dynamic features are computed for the segments. The developed system needs three signatures of one person for the establishment of a personalized template. A database has been collected with 544 signatures of 27 signers for evaluation. The developed system achieved a correct acceptance rate of 78% and a correct rejection rate of 100%.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131146447","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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