AN EFFICIENT DEEP LEARNING APPROACHES FOR ENHANCING IMAGE CLASSIFICATION ACCURACY

Abstract

Digital imagemanipulation takes parttodeform thecontentofa picture in ordertoaccomplish some deceit purposes. Such deceits are acknowledged as forgeries. The precise forgery detection plays a key role in digital images. Image forgery detectionapproaches may be active or passive. Copy-move forgery detection (CMFD) is a passiveBlindimageforgerydetectionmethod.CMFDmainlyimpressesonthespeedandrigorousofthedetection method. To detect CMF, many algorithms are published such as segment based, key pointbasedand block-basedmethods. we are obtaining high accuracy from given data set by using Deep learning algorithm. The proposed method is an innovative and efficient algorithm called Generalized Approximate Reasoning-Based Intelligence Control (GARIC) algorithm. Hence, GARIC deep learning approach is used to detect the presence of falsification in images.The performance of the method is evaluated using classification accuracy