Open AccessDetection of Image Forgery Using Information Standard Method With SVM
Author(s) -
Ahmed Mohammed,
Duraid Hussein Badr,
Fathala Ali
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1818/1/012212
Subject(s) - artificial intelligence , support vector machine , image (mathematics) , computer science , gabor filter , pattern recognition (psychology) , computer vision , discrete cosine transform , image quality , variance (accounting) , accounting , business
Depending on various features, image forgery is now used to enhance and restore images to make them more significant, whereas image forgery is performed by vulnerable people to generate fake truths by tampering images. From large (image) databases, a specified number of images forgery, new mechanism will have implemented to detect systems which is mainly based on two procedures. The first procedure relies on extract features of image through filters (LBP, Gabor, PCA and DCT) to find out its efficiency evaluated using some Statistics Measurements(Mean, Variance) and the second procedure relies on several quality metrics in optimization processes which (PSNR, MSE, AIC) have been calculated to which results in better quality compared to other image by combining selected filters with SVM, and, through experimental test, it was found that this proposed method of detect forgery technique is powerful than the classical detect system. The proposed methodology gives the better accuracy up to 98.5%, to detect and extract all type of forgery, with image enhancement capabilities.