Open AccessJournal Article
Document Analysis and Recognition
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TLDR
This paper addresses current topics about document image understanding from a technical point of view as a survey and proposes methods/approaches for recognition of various kinds of documents.Abstract:
The subject about document image understanding is to extract and classify individual data meaningfully from paper-based documents. Until today, many methods/approaches have been proposed with regard to recognition of various kinds of documents, various technical problems for extensions of OCR, and requirements for practical usages. Of course, though the technical research issues in the early stage are looked upon as complementary attacks for the traditional OCR which is dependent on character recognition techniques, the application ranges or related issues are widely investigated or should be established progressively. This paper addresses current topics about document image understanding from a technical point of view as a survey. key words: document model, top-down, bottom-up, layout structure, logical structure, document types, layout recognitionread more
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References
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Methods and Applications
Ajit Varki,Richard D Cummings,Jeffrey D. Esko,Hudson Freeze,Pamela Stanley,Carolyn R. Bertozzi,Gerald W. Hart,Marilynn E. Etzler +7 more
TL;DR: The aim of the research presented in this thesis is to create new methods for design for manufacturing, by using several approaches of KE, and find the beneficial and less beneficial aspects of these methods in comparison to each other and earlier research.
Journal ArticleDOI
The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping
Claus Bahlmann,Hans Burkhardt +1 more
TL;DR: This work concerns the presentation of the classification/training approach, which is called cluster generative statistical dynamic time warping (CSDTW), a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling.
Proceedings ArticleDOI
Multi-Column Deep Neural Networks for offline handwritten Chinese character classification
Dan Ciresan,Ueli Meier +1 more
TL;DR: Multi-Column Deep Neural Networks achieve state of the art recognition rates on Chinese characters from the ICDAR 2011 and 2013 offline handwriting competitions, approaching human accuracy.
Proceedings ArticleDOI
A rule-based system for document image segmentation
TL;DR: A rule-based system for automatically segmenting a document image into regions of text and nontext is presented and allows easy fine tuning of the algorithmic steps to produce robust rules, to incorporate additional tools (as they become available), and to handle special segmentation needs.