Open Access   Article

Pixel Based Forensic Image Forgery Detection using Signature Resembling Detection and Signature Detection Algorithm

S. B. Pratapur1 , S. D. Chikte2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-10 , Page no. 44-53, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i10.4453

Online published on Oct 31, 2018

Copyright © S. B. Pratapur, S. D. Chikte . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: S. B. Pratapur, S. D. Chikte, “Pixel Based Forensic Image Forgery Detection using Signature Resembling Detection and Signature Detection Algorithm”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.44-53, 2018.

MLA Style Citation: S. B. Pratapur, S. D. Chikte "Pixel Based Forensic Image Forgery Detection using Signature Resembling Detection and Signature Detection Algorithm." International Journal of Computer Sciences and Engineering 6.10 (2018): 44-53.

APA Style Citation: S. B. Pratapur, S. D. Chikte, (2018). Pixel Based Forensic Image Forgery Detection using Signature Resembling Detection and Signature Detection Algorithm. International Journal of Computer Sciences and Engineering, 6(10), 44-53.

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Abstract

The security for the documentations, signature, manually written and mark is challenge errand and essential continuously applications. To address the issues in existing outcomes, the proposed work analyzes the outcomes utilizing three signature forgery detection algorithms, Error Level Analysis, Copy-Paste clone Detection and Fourier based Resembling Detection. Every technique is found to have its own arrangement of points of interest and confinements. An Error Level Analysis gave better outcomes on beforehand compacted, excellent JPEG signatures. The Copy-Paste Clone Detection is exceedingly fruitful on signatures produced utilizing cloning techniques, however the general runtime has considerably higher than alternate strategies, and because of the idea of the calculation false positives is routinely distinguished. Signature Resembling Detection (SRD) worked on a wide assortment of signatures which are taken from genuine signature, transcribed and signature, gives great general outcomes on each dataset, and the rate of false positives is low. The calculation has profoundly proficient in the database absolutely 10 signatures which have brilliant measures are subjected to proposed calculations to segregate amongst innovation and phony archives or transcribed or marks. The proposed work gives a perfect base to a client to decide the most relevant signature fabrication location strategy for their utilization, contingent upon the kinds of signatures that they routinely manage.

Key-Words / Index Term

Signature Resembling Detection, DWT, SVD,SURF,CMDF,SIFT

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