Research Article Open Access

A Novel Digital Image Forgery Detection Method Using SVM Classifier

Abstract

As the use of images have been increasing day by day in our lives, the motivation to create forged images also increases simultaneously. With the introduction of digital technology, digital image has gradually taken the place of the original analog photograph . The forgery of digital image has become more and more simple and indiscoverable. In this paper an extremely common form of image forgery called image splicing is detected by making use of enhanced face extraction techniques and universal classifiers.We propose a forgery detection method that use delicate inconsistencies in the color of the illumination of images. Our approach uses fully automatic methods that requires minimal user interaction .To achieve this, we integrate information from illuminant estimators on image regions of similar material. Human faces are extracted from the illuminant maps . Feature extraction from the extracted faces is done using both edge based and gradient based algorithms. And then combine these complementary cues (texture- and edge-baed) using machine learning late fusion SVM classifier that helps in classification of forged image

V.P.KAVITHA, M.PRIYATHA

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