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Blind Approach for Digital Image Forgery Detection

by Tulsi Thakur, Kavita Singh, Arun Yadav
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 10
Year of Publication: 2018
Authors: Tulsi Thakur, Kavita Singh, Arun Yadav
10.5120/ijca2018916108

Tulsi Thakur, Kavita Singh, Arun Yadav . Blind Approach for Digital Image Forgery Detection. International Journal of Computer Applications. 179, 10 ( Jan 2018), 34-42. DOI=10.5120/ijca2018916108

@article{ 10.5120/ijca2018916108,
author = { Tulsi Thakur, Kavita Singh, Arun Yadav },
title = { Blind Approach for Digital Image Forgery Detection },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 179 },
number = { 10 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 34-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number10/28839-2018916108/ },
doi = { 10.5120/ijca2018916108 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:55:00.529944+05:30
%A Tulsi Thakur
%A Kavita Singh
%A Arun Yadav
%T Blind Approach for Digital Image Forgery Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 10
%P 34-42
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the digital era of where everyone is exposed to a visual imagery in very large extent. Digital images are very convincible way to share information. Due to the rapidly growing field of digital image acquirement and editing software that are impressive as well sophisticated with many advanced features. Manipulation with features of digital image can perform easily with the help of editing tools, which are cost effectively available online or offline and do not leave any visible footprint of tampering with an image. Forgery with the digital image is an unavoidable problem concern with the image authenticity and also with image integrity. Which raising a compulsion to take an immediate action on the forgery of the digital image to verify the authenticity and maintain the integrity. To encounter the problem of authenticity of digital image, this paper proposed a methodology for detection of image splicing forgery using the blind approach i.e., passive method to detect the spliced region in the digital image. In passive approach, there is no provision for the pre-introduction of the watermark and pre-embedded digital signature during the time of image obtainment. This paper mainly concern with the image splicing forgery and it initiate with the DWT (Discrete Wavelet Transform) method, which will decompose the image into sub images and obtain coefficient for each sub image. After that for feature extraction we will use SURF (Speed-Up Robust Features) and finally SVM (Support Vector Machine) will perform classification for splicing forgery detection in digital image.

References
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  23. The dataset mentioned in the paper is freely available to reader at the address [online]. Available: http://forensics.idealtest.org/casiav1/
  24. The dataset mentioned in the paper is freely available to reader at the address [online]. Available: http://forensics.idealtest.org/casiav2/
  25. The dataset mentioned in the paper is freely available to reader at the address [online]. Available: http://www.ee.columbia.edu/ln/dvmm/downloads/AuthSplicedDataSet/AuthSplicedDataSet.htm
Index Terms

Computer Science
Information Sciences

Keywords

Digital image forgery Tampering detection technique Copy-move forgery Splicing forgery Image retouching DWT SVM SURF

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