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Reseach Article

A Survey of Image Processing Techniques for Identification of Printing Technology in Document Forensic Perspective

Published on None 2010 by M. Uma Devi, C. Raghavendra Rao, Arun Agarwal
Recent Trends in Image Processing and Pattern Recognition
Foundation of Computer Science USA
RTIPPR - Number 1
None 2010
Authors: M. Uma Devi, C. Raghavendra Rao, Arun Agarwal
887a502b-111b-4732-8f70-c808260ce643

M. Uma Devi, C. Raghavendra Rao, Arun Agarwal . A Survey of Image Processing Techniques for Identification of Printing Technology in Document Forensic Perspective. Recent Trends in Image Processing and Pattern Recognition. RTIPPR, 1 (None 2010), 9-15.

@article{
author = { M. Uma Devi, C. Raghavendra Rao, Arun Agarwal },
title = { A Survey of Image Processing Techniques for Identification of Printing Technology in Document Forensic Perspective },
journal = { Recent Trends in Image Processing and Pattern Recognition },
issue_date = { None 2010 },
volume = { RTIPPR },
number = { 1 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 9-15 },
numpages = 7,
url = { /specialissues/rtippr/number1/970-93/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Recent Trends in Image Processing and Pattern Recognition
%A M. Uma Devi
%A C. Raghavendra Rao
%A Arun Agarwal
%T A Survey of Image Processing Techniques for Identification of Printing Technology in Document Forensic Perspective
%J Recent Trends in Image Processing and Pattern Recognition
%@ 0975-8887
%V RTIPPR
%N 1
%P 9-15
%D 2010
%I International Journal of Computer Applications
Abstract

This paper discusses about various image processing techniques and tools which are available for identification of printing technologies. Printing technology identification and associated problems in document forensics have been projected as challenges in image processing application. Various image processing approaches based on textures, spatial variation, HSV color space, spatial correlation, and feature based on histogram and some of the pattern recognition methods, like gray level co-occurrence matrix, roughness of the text, perimeter of edge are highlighted. This paper devotes more on one of the recent contribution, namely, Gaussian Variogram Model (GVM) for printer classification.

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Index Terms

Computer Science
Information Sciences

Keywords

Image processing Document forensics-printing technique classification spatial statics