A Modern Approach for Image Forgery Detection using BRICH Clustering based on Normalised Mean and Standard Deviation

with the fast growth of digital technology and user friendly image editing tools, duplicating the contents of digital images becomes easier. The main aim of a digital image forensic is to determine the originality of digital images. Copy move forgery is one of the common methods to forge the digital content. In this paper we introduce a passive method to identify the copy move forgery. It decomposes the image and extracts the moments as feature vector to detect the forgery. The experimental results are studied to demonstrate that the proposed technique detects the forgery and classify the related forged images as clusters based on hierarchical method by BIRCH algorithm. The authentic image even after the post processing operations done on images is identified. Computer vision related with automatic analysis and innovating the useful information from digital information is implemented. It is mainly applied in image understanding.