A Zero-watermarking Image Authentication Scheme Using Zernike Moment and Extreme Learning Machine

摘要：

Based on Zernike moment and extreme learning machine (ELM), a lossless watermarking algorithm against various attacks called zero-watermarking is addressed in this paper. Firstly, image normalization and lifting wavelet transform are used for the invariance of translation and scaling and suppressing of noise. Then Zernike moment magnitudes of training sample images and watermarking image are utilized to construct ELM training modle, whose memory ability enhances the scheme’s performance of resisting attacks. Experimental results prove that the proposed algorithm possesses strong robustness to common signal processings and geometrical distortions.

关键词： Zernike moment extreme learning machine (ELM) zero watermarking

作者: Guangyong Gao Guoping Jiang

作者单位: Center for Control & Intelligence Technology, Nanjing University of Posts and Telecommunications, Na Center for Control & Intelligence Technology, Nanjing University of Posts and Telecommunications, Na

会议类型: 国际会议

会议名称: 2011年无线通信与信号处理国际会议(WCSP 2011)

会议地点: 南京

会议语种:英文

页码: 1-5

在线出版日期: 2011-11-09（万方平台首次上网日期，不代表论文的发表时间）