Title: A novel slant transform-based image feature extract algorithm

Authors: Jinglong Zuo; Delong Cui; Qirui Li

Addresses: College of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming 525000, China ' College of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming 525000, China ' College of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming 525000, China

Abstract: In order to improve the efficiency and simplify the steps of generating an image hashing, a secure and robust image hashing algorithm based on slant transform is proposed in this paper. By employing the coefficients of slant transform, a robust hashing sequence is obtained by preprocessing, feature extracting and post processing. The security of the proposed algorithm is totally dependent on the user-keys, which are saved as secret keys. Several benchmark images are utilised to show the feasibility of the image hashing algorithm. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as JPEG compression, mid-filtering, and rotation. Therefore, the scheme proposed in this paper is suitable for image authentication, content-based image retrieval and digital watermarking, etc.

Keywords: image hashing; slant transform; normalised Hamming distance; encryption keys.

DOI: 10.1504/IJES.2017.084688

International Journal of Embedded Systems, 2017 Vol.9 No.3, pp.202 - 210

Received: 26 Oct 2015
Accepted: 13 Jan 2016
Published online: 21 Jun 2017 *

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