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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 3, September 2014
  4. Texture sparseness for pixel classification of business document images
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 4, December 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 3, September 2014
Learning confidence transformation for handwritten Chinese text recognition
Statistical segmentation and structural recognition for floor plan interpretation : Notation invariant structural element recognition
Mathematical formula identification and performance evaluation in PDF documents
Texture sparseness for pixel classification of business document images
Recognizing handwritten Arabic words using grapheme segmentation and recurrent neural networks
A graph-based approach for segmenting touching lines in historical handwritten documents
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 2, June 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 1, March 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Texture sparseness for pixel classification of business document images

Content Provider SpringerLink
Author Cote, Melissa Branzan Albu, Alexandra
Copyright Year 2014
Abstract Contemporary business documents contain diverse, multi-layered mixtures of textual, graphical, and pictorial elements. Existing methods for document segmentation and classification do not handle well the complexity and variety of contents, geometric layout, and elemental shapes. This paper proposes a novel document image classification approach that distributes individual pixels into four fundamental classes (text, image, graphics, and background) through support vector machines. This approach uses a novel low-dimensional feature descriptor based on textural properties. The proposed feature vector is constructed by considering the sparseness of the document image responses to a filter bank on a multi-resolution and contextual basis. Qualitative and quantitative evaluations on business document images show the benefits of adopting a contextual and multi-resolution approach. The proposed approach achieves excellent results; it is able to handle varied contents and complex document layouts, without imposing any constraint or making assumptions about the shape and spatial arrangement of document elements.
Starting Page 257
Ending Page 273
Page Count 17
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 17
Issue Number 3
e-ISSN 14332825
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2014-02-12
Publisher Place Berlin, Heidelberg
Access Restriction Subscribed
Subject Keyword Business documents Document image segmentation Pixel classification Sparseness Support vector machines Texture Image Processing and Computer Vision Pattern Recognition
Content Type Text
Resource Type Article
Subject Computer Vision and Pattern Recognition Software Computer Science Applications
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