Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28770
Title: DCT-domain global feature and DWT-domain least-squares line fitting based local feature for robust image hashing
Authors: Lei, YQ
Chau, KY
Lu, ZM
Ip, WH 
Keywords: Discrete cosine transform
Discrete wavelet transform
Image authentication
Least-squares line
Robust image hashing
Issue Date: 2010
Publisher: Kumamoto
Source: International journal of innovative computing, information and control, 2010, v. 6, no. 6, p. 2513-2521 How to cite?
Journal: International Journal of Innovative Computing, Information and Control 
Abstract: In this paper, we propose a novel robust image hashing scheme for image authentication based on the Discrete Cosine Transform (DCT) and least-squares line (LSL) fitting of Discrete Wavelet Transform (DWT) coefficients. Firstly, the global feature is extracted from the DC and first nine low-frequency coefficients in every 8×8-sized DCT block of the input image, obtaining the strong robustness to common acceptable manipulations. And then we extract the local feature by fitting DWT coefficients of the image based on the least-squares method (LSM). The proposed local feature can locate the maliciously modified positions. Lastly, the above two kinds of features are combined together to generate the final hash for image authentication. To enforce security, feature extraction is key-dependent in this paper. Experimental results show that the proposed algorithm can resist almost all content-preserving operations such as JPEG compression, filtering, adding noises, and contrast enhancement, while being high sensitive to content tampering.
URI: http://hdl.handle.net/10397/28770
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