Perceptual Image Hashing Based on Weber Local Binary Pattern and Color Angle Representation

Chuan Qin, Yecen Hu, Heng Yao, Xintao Duan, Liping Gao
2019 IEEE Access  
This paper proposes an efficient scheme for generating image hashing by combining the local texture and color angle features. During the stage of texture extraction, using Weber's Law, the difference ratios between the center pixels and their surrounding pixels are calculated and the dimensions of these values are further reduced by applying principal component analysis to the statistical histogram. In the stage of color feature extraction, the color angle of each pixel is computed before
more » ... ional reduction and is carried out using a discrete cosine transform and a significant coefficients selection strategy. The main contribution of this paper is a novel construction for image hashing that incorporates texture and color features by using Weber local binary pattern and color angular pattern. The experimental results demonstrate the efficacy of the proposed scheme, especially for the perceptual robustness against common contentpreserving manipulations, such as the JPEG compression, Gaussian low-pass filtering, and image scaling. Based on the comparisons with the state-of-the-art schemes, receiver operating characteristic curves and integrated histograms of normalized distances show the superiority of our scheme in terms of robustness and discrimination. INDEX TERMS Image hashing, Weber's law, local binary pattern, color angular pattern. 45460 2169-3536
doi:10.1109/access.2019.2908029 fatcat:4fehjmqr45gi7cs6gmfp32kk3u