Perceptual hashing of color images using hypercomplex representations

Abstract

This paper presents a new perceptual image hashing approach that exploits the image color information using hypercomplex (quaternionic) representations. Unlike grayscale-based techniques, the proposed approach preserves the color interaction between the image components that have a significant contribution in the generated perceptual image hash codes. Having a robust image hash function optimizes a wide range of applications including content-based retrieval, image authentication, and image watermarking. Initially, the input color image is processed in a “holistic” manner using the hypercomplex representation where the red, green and blue (RGB) components are handled as a single entity. Then, non-overlapping 8 × 8 image blocks are processed using the Quaternion Fourier transform (QFT). Binary image hash codes are generated by comparing the block mean frequency energy to the global mean frequency energy. For retrieval purposes, the Hamming distance (HD) is used as the comparison metric to retrieve perceptually similar images. The performance of the proposed perceptual hashing for color image is compared to that based on the conventional complex Fourier transform (CFT). Simulation results clearly indicate the superior retrieval performance of the proposed QFT-based perceptual hashing technique in term of HD values of intra-and inter-class image samples. Moreover, the performance improvement of the QFT-based technique is achieved at a computational complexity similar to the CFT-based scheme.