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Digital Image Forgery Detection based on Texture Feature and Clustering Technique

by Upendra Ujjainiya, Shaila Chugh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 11
Year of Publication: 2016
Authors: Upendra Ujjainiya, Shaila Chugh
10.5120/ijca2016911225

Upendra Ujjainiya, Shaila Chugh . Digital Image Forgery Detection based on Texture Feature and Clustering Technique. International Journal of Computer Applications. 147, 11 ( Aug 2016), 21-24. DOI=10.5120/ijca2016911225

@article{ 10.5120/ijca2016911225,
author = { Upendra Ujjainiya, Shaila Chugh },
title = { Digital Image Forgery Detection based on Texture Feature and Clustering Technique },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 11 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 21-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number11/25698-2016911225/ },
doi = { 10.5120/ijca2016911225 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:51:39.931210+05:30
%A Upendra Ujjainiya
%A Shaila Chugh
%T Digital Image Forgery Detection based on Texture Feature and Clustering Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 11
%P 21-24
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The image forgery detection is important tools in digital multi-media analysis. Now a day’s digital multi-media faced a problem of copy paste and tampering by different multi-media authoring tools. The tampered and copy paste image change the actual scenario of original image and its illegal process in current scenario of multi-media. For the detection of image forgery various pixel and transform based method are applied. The applied method is better in some detection and estimation, but faced a certain limitation. In this paper proposed texture based image forgery detection. The texture based image forgery detection is very efficient in terms of detection ratio. For the extraction of texture feature used discrete wavelet transform function. For the generation of block used partition clustering technique. the partition clustering technique creates the block of original and forged image. The proposed algorithm is simulated in MATLAB software and used very famous dataset MFIC2000.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Forgery DWT Cluster Segmentation Texture

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