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Volume: 22 | Article ID: art00066_1
Image
Wavelet-Based Document Enhancement
Mohamed N. Ahmed
Ahmed Eid
  DOI :  10.2352/ISSN.2169-4451.2006.22.1.art00066_1  Published Online :  January 2006
Abstract

We present in this paper a new system to segment and label document images by combining statistical and multiscale view of different image components. Texture of text, halftone and images are characterized by modeling the distribution of the wavelet detail coefficients using a mixture of k Gaussians. Model parameters are then estimated using the expectation maximization (EM) algorithm. Using the proposed alogrithm, halftone areas were succefully differentiated from text regions

Journal Title : NIP & Digital Fabrication Conference
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
Subject Areas :
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 DOI 10.2352/ISSN.2169-4451.2006.22.1.art00066_1
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  Cite this article 

Mohamed N. Ahmed, Ahmed Eid, "Wavelet-Based Document Enhancement"  in Proc. IS&T Int'l Conf. on Digital Printing Technologies (NIP22),  2006,  pp 256 - 260,  https://doi.org/10.2352/ISSN.2169-4451.2006.22.1.art00066_1

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Copyright © Society for Imaging Science and Technology 2006
72010410
NIP & Digital Fabrication Conference
nip digi fabric conf
2169-4451
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2169-4451(20060101)2006:1L.256;1-
nip_v2006n1/splitsection66.xml
/ist/nipdf/2006/00002006/00000001/art00066
Articles
Wavelet-Based Document Enhancement
AhmedMohamed N.
EidAhmed
01012006
2006
1
256
260
2006
We present in this paper a new system to segment and label document images by combining statistical and multiscale view of different image components. Texture of text, halftone and images are characterized by modeling the distribution of the wavelet detail coefficients using a mixture of k Gaussians. Model parameters are then estimated using the expectation maximization (EM) algorithm. Using the proposed alogrithm, halftone areas were succefully differentiated from text regions