广西师范大学学报（自然科学版） ›› 2016, Vol. 34 ›› Issue (4): 9-18.doi: 10.16088/j.issn.1001-6600.2016.04.002

• 广西高校优秀中青年骨干教师培养工程论坛 • 上一篇    下一篇

基于PCA特征距离的图像哈希算法

唐振军1,2,杨帆1,2,黄紫晴1,2,劳欢1,2   

  1. 1.广西师范大学广西多源信息挖掘与安全重点实验室,广西桂林541004;
    2.广西师范大学计算机科学与信息工程学院,广西桂林541004
  • 收稿日期:2016-06-19 出版日期:2016-07-18 发布日期:2018-07-18
  • 通讯作者: 唐振军(1979—),男,广西桂平人,广西师范大学教授,博士。E-mail:tangzj230@163.com
  • 基金资助:
    国家自然科学基金资助项目(61300109, 61363034, 61562007);广西自然科学基金资助项目(2015GXNSFDA139040);广西“八桂学者”工程专项经费资助项目;广西高等学校优秀中青年骨干教师培养工程资助项目(GXGQ012013059);广西多源信息挖掘与安全重点实验室系统性研究基金资助项目(15-A-02-02, 14-A-02-02,13-A-03-01)

Image Hashing Algorithm Based on PCA Feature Distance

TANG Zhenjun1,2, YANG Fan1,2, HUANG Ziqing1,2, LAO Huan1,2   

  1. 1. Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin Guangxi 541004, China;
    2. College of Computer Science and Information Technology, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2016-06-19 Online:2016-07-18 Published:2018-07-18

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摘要： 本文将主成分分析(PCA)应用于图像哈希,设计基于特征距离的感知哈希算法。该算法从规范化图像中构造适合于数据降维的二次图像,接着对其进行PCA处理,用PCA降维特征的距离生成哈希序列。实验结果表明本文算法的接收机操作特性曲线的分类性能优于现有的3种哈希算法。大规模图像库的拷贝检测显示,本文算法有较好的拷贝检测性能。

关键词: 感知哈希函数, 主成分分析, 数据降维, 图像拷贝检测, 图像检索

Abstract: Principal component analysis (PCA) is applied to image hashing algorithm and a perceptual hashing algorithm based on characteristic distance is proposed. In the proposed algorithm, a secondary image suitable for data dimension reduction is first constructed from the normalized image. Then, PCA is used to process secondary image, and the distance between PCA features is finally exploited to form image hash. Experimental results illustrate that classification performance of the proposed algorithm measured with receiver operating characteristics (ROC) curve is better than those of three existing hashing algorithms. Copy detection under a large-scale image database shows that the proposed algorithm has good performance in detecting image copies.

Key words: perceptual hash function, principal component analysis (PCA), data dimension reduction, image copy detection, image retrieval

中图分类号: 

  • TP391
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