Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: IResearch Article Semi-Fragile Zernike Moment-Based Image Watermarking for Authentication | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 341856 17 pages doi 2010 341856 Research Article Semi-Fragile Zernike Moment-Based Image Watermarking for Authentication Hongmei Liu 1 Xinzhi Yao 2 and Jiwu Huang1 1 Department of Electronics and Communication Sun Yat-sen University Guangzhou 510006 China 2 Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Correspondence should be addressed to Hongmei Liu isslhm@ Received 30 November 2009 Revised 17 May 2010 Accepted 6 July 2010 Academic Editor Jin-Hua She Copyright 2010 Hongmei Liu et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We propose a content-based semi-fragile watermarking algorithm for image authentication. In content-based watermarking scheme for authentication one of the most challenging issues is to define a computable feature vector that can capture the major content characteristics. We identify Zernike moments of the image to generate feature vector and demonstrate its good robustness and discriminative capability for authentication. The watermark is generated by quantizing Zernike moments magnitudes ZMMs of the image and embedded into DWT Discrete Wavelet Transform subband. It is usually hard to locate the tampered area by using global feature in the content-based watermarking scheme. We propose a structural embedding method to locate the tampered areas by using the separability of Zernike moments-based feature vector. The authentication process does not need the original feature vector. By using the semi-fragilities of the feature vector and the watermark the proposed authentication scheme is robust to content-preserved processing while being fragile to malicious attacks. As an application of our algorithm we apply it
