scholarly journals Evaluation of Image Forgery Detection Using Multi-scale Weber Local Descriptors

2013 ◽  
pp. 416-424 ◽  
Author(s):  
Sahar Q. Saleh ◽  
Muhammad Hussain ◽  
Ghulam Muhammad ◽  
George Bebis
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Local Descriptors ◽  
Multi Scale ◽  
Image Forgery Detection

scholarly journals Image Forgery Detection by using Machine Learning

2019 ◽  
Vol 8 (6S4) ◽  
pp. 561-563 ◽  
Keyword(s):  
Machine Learning ◽  
Svm Classifier ◽  
Forgery Detection ◽  
Two Phase ◽  
Image Forgery ◽  
Local Descriptors ◽  
Image Structure ◽  
Image Forgery Detection

Dense local descriptors and AI havebeen utilized with achievement in a couple of employments, as classificationof surfaces, steganalysis, and bowing zone. We build up a newimage counterfeit marker creating unequivocal descriptors recentlyproposed in the steganalysis field reasonably joining some of suchdescriptors, and redesigning a SVM classifier on the availabletraining set. The issue with the present making is that majorityof them see certain highlights in pictures changed by a particular tamperingmethod, (for example, duplicate move, joining, and so forth). This proposes the structure does notwork always transversely over different evolving frameworks. Mix of no under two pictures to make a completely phony picture is known as Image structure. It winds up being difficult to disengage between certified picture and phony picture in light of the closeness of different astounding changing programming endeavors. In this paper, we propose a two phase imperative altering way to deal with oversee direct learn featuresin referencing to see changed pictures in various pictureformats

scholarly journals Image forgery detection using multi-resolution Weber local descriptors

Eurocon 2013 ◽  
2013 ◽  
Author(s):  
Muhammad Hussain ◽  
Ghulam Muhammad ◽  
Sahar Q. Saleh ◽  
Anwar M. Mirza ◽  
George Bebis
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Local Descriptors ◽  
Image Forgery Detection

Image Forgery Detection Based on Trigonometric Transforms

2019 ◽  
Vol 28 (2) ◽  
pp. 203-216
Author(s):  
Faten Al-Azrak ◽  
Moawad Dessouky ◽  
Fathi Abd El-Samie ◽  
Ahmed Elkorany ◽  
Zeinab Elsharkawy
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Image Forgery Detection ◽  
Trigonometric Transforms

Image forgery detection using Gabor filters and DCT

2014 ◽  
Author(s):  
Ghulam Muhammad ◽  
M. Solaiman Dewan ◽  
M. Moniruzzaman ◽  
Muhammad Hussain ◽  
M. Nurul Huda
Keyword(s):  
Gabor Filters ◽  
Forgery Detection ◽  
Image Forgery ◽  
Image Forgery Detection
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