Pub Date : 2003-08-03DOI: 10.1109/ICDAR.2003.1227822
Xiaofan Lin
This paper introduces a novel journal splittingalgorithm. It takes full advantage of various kinds ofinformation such as text match, layout and page numbers.The core procedure is a highly efficient text-miningalgorithm, which detects the matched phrases between thecontent pages and the title pages of individual articles.Experiments show that this algorithm is robust and ableto split a wide range of journals, magazines and books.
{"title":"Text-mining based journal splitting","authors":"Xiaofan Lin","doi":"10.1109/ICDAR.2003.1227822","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227822","url":null,"abstract":"This paper introduces a novel journal splittingalgorithm. It takes full advantage of various kinds ofinformation such as text match, layout and page numbers.The core procedure is a highly efficient text-miningalgorithm, which detects the matched phrases between thecontent pages and the title pages of individual articles.Experiments show that this algorithm is robust and ableto split a wide range of journals, magazines and books.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116961984","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227776
H. Legal-Ayala, J. Facon
This article describes a new segmentation bythresholding approach based on learning. The methodconsists in learning to threshold correctly submitting bothan image and its ideal thresholded version. From thisstage it is generated a decision matrix for each pixel andeach gray level that is re-utilized at the moment of thenew images segmentation. The new image is thresholdedby means of a new strategy based on the nearestneighbors, that seeks, for each pixel of this new image,the best solution in the decision matrix. Performed testson handwritten documents showed promising results. Interms of quality of the results, the developed technique isequal or superior to the traditional segmentation bythresholding techniques, with the advantage that the onediscussed here does not requires the use of heuristicparameters.
{"title":"Image segmentation by learning approach","authors":"H. Legal-Ayala, J. Facon","doi":"10.1109/ICDAR.2003.1227776","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227776","url":null,"abstract":"This article describes a new segmentation bythresholding approach based on learning. The methodconsists in learning to threshold correctly submitting bothan image and its ideal thresholded version. From thisstage it is generated a decision matrix for each pixel andeach gray level that is re-utilized at the moment of thenew images segmentation. The new image is thresholdedby means of a new strategy based on the nearestneighbors, that seeks, for each pixel of this new image,the best solution in the decision matrix. Performed testson handwritten documents showed promising results. Interms of quality of the results, the developed technique isequal or superior to the traditional segmentation bythresholding techniques, with the advantage that the onediscussed here does not requires the use of heuristicparameters.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117259280","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227840
A. Seropian, M. Grimaldi, N. Vincent
Our aim is to achieve writer identification processthanks to a fractal analysis of handwriting style. For eachwriter, a set of characteristics is extracted. They arespecific to the writer. Advantage is taken from theautosimilarity properties that are present in one'shandwriting. In order to do that, some invariant patternscharacterizing the writing are extracted. During thetraining step these invariant patterns appear along afractal compression process, then they are organized in areference base that can be associated with the writer.This base allows to analyze an unknown writing thewriter of which has to be identified. A Pattern Matchingprocess is performed using all the reference basessuccessively. The results of this analyze are estimatedthrough the signal to noise ratio. Thus, the signal to noiseratio according to a set of bases identifies the unknowntext's writer.
{"title":"Writer identification based on the fractal construction of a reference base","authors":"A. Seropian, M. Grimaldi, N. Vincent","doi":"10.1109/ICDAR.2003.1227840","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227840","url":null,"abstract":"Our aim is to achieve writer identification processthanks to a fractal analysis of handwriting style. For eachwriter, a set of characteristics is extracted. They arespecific to the writer. Advantage is taken from theautosimilarity properties that are present in one'shandwriting. In order to do that, some invariant patternscharacterizing the writing are extracted. During thetraining step these invariant patterns appear along afractal compression process, then they are organized in areference base that can be associated with the writer.This base allows to analyze an unknown writing thewriter of which has to be identified. A Pattern Matchingprocess is performed using all the reference basessuccessively. The results of this analyze are estimatedthrough the signal to noise ratio. Thus, the signal to noiseratio according to a set of bases identifies the unknowntext's writer.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115903434","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227669
Sriram Ramachandran, R. Kashi
There have been recent improvements in document technologies like the standardization of object interfaces to access and manipulate the properties of Web documents. There has also been significant progress in pen based computing for recognition of digital ink in desktops, tablets and handheld devices. These have necessitated a need for further research on annotation architectures for digital documents, specifically pen-based annotation systems. This paper presents an attempt to leverage the new standards of DHTML and W3C DOM that are being gradually implemented by popular browsers, to build a prototype of an ink annotation system with common components across browsers. One of the primary goals in this study is to semantically link ink data with underlying document elements like text and images. The system has three components: a) ink capture and rendering b) Ink Understanding, which recognizes and associates ink with the underlying document; and c) Ink storage and retrieval.
{"title":"An architecture for ink annotations on Web documents","authors":"Sriram Ramachandran, R. Kashi","doi":"10.1109/ICDAR.2003.1227669","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227669","url":null,"abstract":"There have been recent improvements in document technologies like the standardization of object interfaces to access and manipulate the properties of Web documents. There has also been significant progress in pen based computing for recognition of digital ink in desktops, tablets and handheld devices. These have necessitated a need for further research on annotation architectures for digital documents, specifically pen-based annotation systems. This paper presents an attempt to leverage the new standards of DHTML and W3C DOM that are being gradually implemented by popular browsers, to build a prototype of an ink annotation system with common components across browsers. One of the primary goals in this study is to semantically link ink data with underlying document elements like text and images. The system has three components: a) ink capture and rendering b) Ink Understanding, which recognizes and associates ink with the underlying document; and c) Ink storage and retrieval.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432751","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227734
Yefeng Zheng, Huiping Li, D. Doermann
In this paper we address the problem of the identification of text from noisy documents. We segment and identify handwriting from machine printed text because 1) handwriting in a document often indicates corrections, additions or other supplemental information that should be treated differently from the main body or body content, and 2) the segmentation and recognition techniques for machine printed text and handwriting are significantly different. Our novelty is that we treat noise as a separate class and model noise based on selected features. Trained Fisher classifiers are used to identify machine printed text and handwriting from noise. We further exploit context to refine the classification. A Markov random field (MRF) based approach is used to model the geometrical structure of the printed text, handwriting and noise to rectify the mis-classification. Experimental results show our approach is promising and robust, and can significantly improve the page segmentation results in noise documents.
{"title":"Text identification in noisy document images using Markov random model","authors":"Yefeng Zheng, Huiping Li, D. Doermann","doi":"10.1109/ICDAR.2003.1227734","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227734","url":null,"abstract":"In this paper we address the problem of the identification of text from noisy documents. We segment and identify handwriting from machine printed text because 1) handwriting in a document often indicates corrections, additions or other supplemental information that should be treated differently from the main body or body content, and 2) the segmentation and recognition techniques for machine printed text and handwriting are significantly different. Our novelty is that we treat noise as a separate class and model noise based on selected features. Trained Fisher classifiers are used to identify machine printed text and handwriting from noise. We further exploit context to refine the classification. A Markov random field (MRF) based approach is used to model the geometrical structure of the printed text, handwriting and noise to rectify the mis-classification. Experimental results show our approach is promising and robust, and can significantly improve the page segmentation results in noise documents.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121871123","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227696
R. Kasturi
Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to be caused by text. The method is tested on a captured video of a typical street scene.
{"title":"Detection of text marks on moving vehicles","authors":"R. Kasturi","doi":"10.1109/ICDAR.2003.1227696","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227696","url":null,"abstract":"Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to be caused by text. The method is tested on a captured video of a typical street scene.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121880873","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227826
S. Srihari, C. Tomai, Bin Zhang, Sangjik Lee
The analysis of handwritten documents from the view-pointof determining their writership has great bearing onthe criminal justice system. In many cases, only a limitedamount of handwriting is available and sometimes it consistsof only numerals. Using a large number of handwrittennumeral images extracted from about 3000 samples writtenby 1000 writers, a study of the individuality of numerals foridentification/verification purposes was conducted. The individualityof numerals was studied using cluster analysis.Numerals discriminability was measured for writer verification.The study shows that some numerals present a higherdiscriminatory power and that their performances for theverification/identification tasks are very different.
{"title":"Individuality of numerals","authors":"S. Srihari, C. Tomai, Bin Zhang, Sangjik Lee","doi":"10.1109/ICDAR.2003.1227826","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227826","url":null,"abstract":"The analysis of handwritten documents from the view-pointof determining their writership has great bearing onthe criminal justice system. In many cases, only a limitedamount of handwriting is available and sometimes it consistsof only numerals. Using a large number of handwrittennumeral images extracted from about 3000 samples writtenby 1000 writers, a study of the individuality of numerals foridentification/verification purposes was conducted. The individualityof numerals was studied using cluster analysis.Numerals discriminability was measured for writer verification.The study shows that some numerals present a higherdiscriminatory power and that their performances for theverification/identification tasks are very different.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129982815","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227679
Molly L. Boose, D. B. Shema, Lawrence S. Baum
This paper discusses a scalable solution for integrating legacy illustrated parts drawings into a Class IV Interactive Electronic Technical Manual (IETM) (1995). An IETM is an interactive electronic version of a system's technical manuals such as for a commercial airplane or a military helicopter. It contains the information a technician needs to do her job including troubleshooting, vehicle maintenance and repair procedures. A Class IV IETM is an IETM that is authored and managed directly via a database. The end-user system optimizes viewing and navigation, minimizing the need for users to browse and search through large volumes of data. The Boeing Company has hundreds of thousands of illustrated parts drawings for both commercial and military vehicles. As Boeing migrates to Class IV IETM systems, it is necessary to incorporate existing illustrated parts drawings into the new systems. Manually re-authoring the drawings to bring them up to the level of a Class IV IETM is prohibitively expensive. Our solution is to provide a batch-processing system that performs the required modifications to the raster images and automatically updates the IETM database.
{"title":"A scalable solution for integrating illustrated parts drawings into a Class IV Interactive Electronic Technical Manual","authors":"Molly L. Boose, D. B. Shema, Lawrence S. Baum","doi":"10.1109/ICDAR.2003.1227679","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227679","url":null,"abstract":"This paper discusses a scalable solution for integrating legacy illustrated parts drawings into a Class IV Interactive Electronic Technical Manual (IETM) (1995). An IETM is an interactive electronic version of a system's technical manuals such as for a commercial airplane or a military helicopter. It contains the information a technician needs to do her job including troubleshooting, vehicle maintenance and repair procedures. A Class IV IETM is an IETM that is authored and managed directly via a database. The end-user system optimizes viewing and navigation, minimizing the need for users to browse and search through large volumes of data. The Boeing Company has hundreds of thousands of illustrated parts drawings for both commercial and military vehicles. As Boeing migrates to Class IV IETM systems, it is necessary to incorporate existing illustrated parts drawings into the new systems. Manually re-authoring the drawings to bring them up to the level of a Class IV IETM is prohibitively expensive. Our solution is to provide a batch-processing system that performs the required modifications to the raster images and automatically updates the IETM database.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129323292","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227859
Sanaul Hoque, H. Selim, G. Howells, M. Fairhurst, F. Deravi
A novel strategy for the representation and manipulationof distributed documents, potentially complex andheterogeneous, is presented in this paper. The documentunder the proposed model is represented in a hierarchicalstructure. Associated metadata' describes the flexiblehierarchy with the scope of dynamically restructuring thetree at runtime. All useful functionals can also be includedwithin the hierarchy to minimize reliance on externalprograms in manipulating sensitive data. Thisgives the proposed model two key properties: generality(capable of representing any document format includingfuture innovations) and autonomy (non-reliance on externalprograms). The model also allows incorporation ofadditional features for security and access control. Biometricperson authentication measures are introduced. Abrief example illustrates the key ideas.
{"title":"SAGENT: a novel technique for document modeling for secure access and distribution","authors":"Sanaul Hoque, H. Selim, G. Howells, M. Fairhurst, F. Deravi","doi":"10.1109/ICDAR.2003.1227859","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227859","url":null,"abstract":"A novel strategy for the representation and manipulationof distributed documents, potentially complex andheterogeneous, is presented in this paper. The documentunder the proposed model is represented in a hierarchicalstructure. Associated metadata' describes the flexiblehierarchy with the scope of dynamically restructuring thetree at runtime. All useful functionals can also be includedwithin the hierarchy to minimize reliance on externalprograms in manipulating sensitive data. Thisgives the proposed model two key properties: generality(capable of representing any document format includingfuture innovations) and autonomy (non-reliance on externalprograms). The model also allows incorporation ofadditional features for security and access control. Biometricperson authentication measures are introduced. Abrief example illustrates the key ideas.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129488369","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 : 2003-08-03DOI: 10.1109/ICDAR.2003.1227666
A. Schenker, Mark Last, H. Bunke, A. Kandel
In this paper we describe work relating to classification of Web documents using a graph-based model instead of the traditional vector-based model for document representation. We compare the classification accuracy of the vector model approach using the k-nearest neighbor (k-NN) algorithm to a novel approach which allows the use of graphs for document representation in the k-NN algorithm. The proposed method is evaluated on three different Web document collections using the leave-one-out approach for measuring classification accuracy. The results show that the graph-based k-NN approach can outperform traditional vector-based k-NN methods in terms of both accuracy and execution time.
{"title":"Classification of Web documents using a graph model","authors":"A. Schenker, Mark Last, H. Bunke, A. Kandel","doi":"10.1109/ICDAR.2003.1227666","DOIUrl":"https://doi.org/10.1109/ICDAR.2003.1227666","url":null,"abstract":"In this paper we describe work relating to classification of Web documents using a graph-based model instead of the traditional vector-based model for document representation. We compare the classification accuracy of the vector model approach using the k-nearest neighbor (k-NN) algorithm to a novel approach which allows the use of graphs for document representation in the k-NN algorithm. The proposed method is evaluated on three different Web document collections using the leave-one-out approach for measuring classification accuracy. The results show that the graph-based k-NN approach can outperform traditional vector-based k-NN methods in terms of both accuracy and execution time.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128232333","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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