文献类型：期刊文献

英文题名：A novel robust image-hashing method for content authentication

作者：Jiang, Cuiling[1]; Pang, Yilin[1]; Wu, Anwen[1]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China

年份：2015

起止页码：22

外文期刊名：Proceedings - 2015 International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2015

收录：EI(收录号：20161702301898)

语种：英文

外文关键词：Wavelet transforms - Gaussian noise (electronic) - Digital forensics - Hash functions - Authentication - Image compression - Search engines

摘要：Image hash functions find extensive application in content authentication, database search, and digital forensic. This paper develops a novel robust image-hashing method based on genetic algorithm (GA) and Back Propagation (BP) Neural Network for content authentication. Lifting wavelet transform is used to extract image low frequency coefficients to create the image feature matrix. A GA-BP network model is constructed to generate image-hashing code. Experimental results demonstrate that the proposed hashing method is robust against random attack, JPEG compression, additive Gaussian noise, and so on. Receiver operating characteristics (ROC) analysis over a large image database reveals that the proposed method significantly outperforms other approaches for robust image hashing. ? 2015 IEEE.