A novel image hashing scheme with perceptual robustness using block truncation coding

In this paper, we propose a novel perceptual image hashing scheme based on block truncation coding (BTC). In the proposed scheme, the pre-processing is first applied on original image through bilinear interpolation, Gaussian low-pass filtering, and singular value decomposition (SVD) to construct a secondary image for regularization. Then, BTC is conducted on the secondary image to extract perceptual image features, and the low and high reconstruction levels and the feature matrix of corresponding binary map after the computation of center-symmetrical local binary pattern (CSLBP) are compressed with quantization and data dimensionality reduction of PCA to produce the final compact binary hash. Experimental results demonstrate that the proposed scheme has the satisfactory performances of robustness, anti-collision, and security. (C) 2016 Elsevier Inc. All rights reserved.