Perceptual Hash Function based on Scale-Invariant Feature Transform and Singular Value Decomposition

It is almost impossible to distinguish between the original and manipulated images subjectively due to the growth in technologies. The main aim of this paper is to develop a robust hash function, which can withstand legitimate modifications. A robust hash algorithm based on scale-invariant feature transform (SIFT) and singular value decomposition (SVD) is being proposed in this paper. Hash values are generated from the maximum singular values obtained after applying SVDs to the SIFT key-points mapped non-overlapping blocks of pixels. The experimental result shows that the proposed hashing method is robust against the various attacks.