抽象的な

Image Forgery Detection Using Svm Classifier

Anita Sahani, K.Srilatha

In this paper, a method is developed for detecting image forgery including removal, insertion, and replacement of objects. SVM classifier is used which have similar functional form to neural networks. Image, texture and pixel value based features are extracted and analyzed from the images. Then hash values are calculated for these features. The process consists of two phases which are training phase and a testing phase. SVM classifier is trained with a set of images. SVM classifiers are used to classify the images as genuine or forged. For the secure use, RSA algorithm can be applied so that only authorized person can run the application to check whether the given query image is genuine or forged.