›› 2015, Vol. 28 ›› Issue (10): 41-.

• 论文 • 上一篇    下一篇

基于Zernike矩和熵的图像感知哈希算法

张大兴,陈娟娟,邵伯仲   

  1. (杭州电子科技大学 计算机学院,浙江 杭州 310018)
  • 出版日期:2015-10-15 发布日期:2015-10-29
  • 作者简介:张大兴(1971—),男,博士,副教授。研究方向:多媒体信息安全。E-mail:dxzhang@hdu.edu.cn。陈娟娟(1989—),女,硕士研究生。研究方向:多媒体信息安全。
  • 基金资助:
    国家自然科学基金资助项目(61272391)

Perceptual Image Hashing Based on Zernike Moment and Entropy

ZHANG Daxing,CHEN Juanjuan,SHAO Bozhong   

  1. (School of Computer Science,Hangzhou Dianzi University,Hangzhou 310018,China)
  • Online:2015-10-15 Published:2015-10-29

摘要: 提出了基于Zernike矩和熵特征的数字图像感知哈希算法。算法利用Zernike矩计算参考方向,以计算等面积环块和等角度扇形块内的熵作为感知特征,并通过量化处理构造哈希序列。算法利用哈希码之间的欧氏距离作为图像内容相似性的判定依据。实验结果表明,该算法对加性噪声、JEPG压缩、几何变换等操作具有较好的鲁棒性,且对于内容不同的图像有较好的区分度。

关键词: 感知哈希, 熵特征, Zernike矩, 鲁棒性, 区分性

Abstract: A novel perceptual image hashing based on entropies features and Zernike moments has been proposed in this paper.This approach calculates the reference orientation by Zernike moments and the entropies of equal area ring and angle as perceptual features.Then the hash sequence is generated after quantization.The Euclidean distance is used to measure content similarity in the scheme.The experimental results show that the proposed algorithm has good robustness on additive noise,JPEG compression,geometric operations and good discrimination for different images.

Key words: perceptual hashing;entropies features;Zernike moment;robustness,discrimination

中图分类号: 

  • TN911.73