A perceptual image hashing method via SIFT and PCA

TLDR: Test results indicate that the proposed method is robust to various types of attacks such as image rotation, illumination change and filtering, etc.

Abstract: This paper presents a novel perceptual hashing method based on scale invariant feature transform(SIFT) and principal component analysis(PCA).SIFT features are invariant to image scaling and rotation,and stable to common image processing.Through the detailed analysis of two-stage framework of generating hash,SIFT is used to capture the local features of image.PCA is used to compress features information.Final hash is generated by summing PCA basis of each key point.The method uses pesduo-randomly processing for enhancing security of the algorithm.The similarity of images is determined by hash normalization correlation.Test results indicate that the proposed method is robust to various types of attacks such as image rotation,illumination change and filtering,etc.It is superior in image identification compared with the image hashing using non-negative matrix factorization.