基于离散余弦变换的鲁棒感知图像哈希技术

对现有感知图像哈希的生成方法进行深入研究,分析该方法存在的不足之处。分别介绍离散余弦变换、Watson视觉模型和混沌模型的原理和特点,提出将这3种模型进行融合来设计感知图像哈希的生成方法。该方法采用离散余弦变换提取图像特征,对比敏感表对特征向量进行处理并用Logistic方程作为混沌序列发生器进行加密,最后采用预测差分方法进行量化编码。试验结果表明:该方法可以抵抗内容保持的修改操作,并具有较强的鲁棒性、安全性和检索性,且冲突概率降低到10-7数量级。该技术在图像认证、版权保护、安全和基于内容的图像检索等方面有应用价值。

Robust Image Perceptual Hashing Technology Based on Discrete Cosine Transform

Current methods about perceptual hashing were researched and the defects of them were analyzed.Principles and characters of discrete cosine transform,Watson visual model and chaotic model were introduced in detail.A new method about perceptual image hashing which combined the characteristics of the three models was designed.This method used discrete cosine transform to feature extraction from image,eigenvector was handled by contrast sensitivity table,Logistic equation was used as chaos sequence generator to encrypt and prediction differential method was used to quantization coding.Experimental results indicated that the method could resist the content-preserving modifications.The method possessed strong robustness,safety and retrieval ability,and the collision rate decreases to level.Therefore,the method could be used to image authentication,copyright protection,image security and content-based image retrieval and so on.