Adaptive just-noticeable difference profile for image hashing. (March 2021) - Khan, Muhammad Farhan; Monir, Syed Muhammad; Naseem, Imran; Khan, Bilal Muhammad
Abstract: A novel algorithm to extract image features related to human perception of colors is presented in this paper. The proposed profile is based on the generation of a lookup table with thresholds for just-noticeable color difference against all possible colors from RGB color gamut. The profile is further used to reduce the computational cost of image hashing. The host color image is scanned to generate the maximum magnitude difference profile. The lookup table is then used for thresholding of magnitude differences to generate the binary adaptive just-noticeable difference profile. The generated profile can be used for image watermarking, hashing and similar image processing applications. Performance of the proposed profile has been tested for image hashing. Average similarity of 0.97 for 66 tampered versions of 42 host images and discrimination of 0.138 among 79, 800 different image hash pairs have been obtained while area under receiver operating characteristic curve is 0.9980. Graphical abstract: Highlights: Just-noticeable difference in Lab color model is used for RGB perceptual thresholding. Thresholds against RGB image pixels form adaptive just-noticeable difference profile. Perceptual profile base on adaptive JND features produces robust binary features. Robust binary features of host image are used for image hashing and watermarking.