Copy Move Forgery Detection Using Glcm Based Statistical Features

The features Gray Level Co-occurrence Matrix (GLCM) are mostly explored in Face Recognition and CBIR. GLCM technique is explored here for Copy-Move Forgery Detection. GLCMs are extracted from all the images in the database and statistics such as contrast, correlation, homogeneity and energy are derived. These statistics form the feature vector. Support Vector Machine (SVM) is trained on all these features and the authenticity of the image is decided by SVM classifier. The proposed work is evaluated on CoMoFoD database, on a whole 1200 forged and processed images are tested. The performance analysis of the present work is evaluated with the recent methods.