An Image Hashing Algorithm For Authentication With Multi-Attack Reference Generation And Adaptive Thresholding

Image hashing-based authentication methods have been widely studied with continuous advancements owing to the speed and memory efficiency. However, reference hash generation and threshold setting, which are used for similarity measures between original images and corresponding distorted version, are important but less considered by most of existing models. In this paper, we propose an image hashing method based on multi-attack reference generation and adaptive thresholding for image authentication. We propose to build the prior information set based on the help of multiple virtual prior attacks, and present a multi-attack reference generation method based on hashing clusters. The perceptual hashing algorithm was applied to the reference/queried image to obtain the hashing codes for authentication. Furthermore, we introduce the concept of adaptive thresholding to account for variations in hashing distance. Extensive experiments on benchmark datasets have validated the effectiveness of our proposed method.