首页 | 本学科首页   官方微博 | 高级检索  
     

利用SIFT特征的非对称匹配图像拼接盲检测
引用本文:杜振龙,杨凡,李晓丽,郭延文,沈钢纲.利用SIFT特征的非对称匹配图像拼接盲检测[J].中国图象图形学报,2013,18(4):442-890.
作者姓名:杜振龙  杨凡  李晓丽  郭延文  沈钢纲
作者单位:1. 南京工业大学电子与信息工程学院,南京,210009
2. 南京大学软件新技术国家重点实验室,南京,210000
基金项目:国家自然科学基金项目(61073098);教育部高等学校博士点基金项目(20113221120003);江苏省六大人才高峰基金项目(2012-WLW-023);江苏省自然科学基金项目(BK2009081);江苏省科技支撑计划项目(SBE201077457);江苏省高校自然科学基金项目(09KJB520006,11KJD520007);南京大学软件新技术国家重点实验室开放基金项目(KFKT2008B15);东南大学计算机网络和信息集成教育部重点实验室项目(K93-9-2010-04)
摘    要:复制粘贴伪造图像鉴定检测图像中的疑似相似区域。传统的逐像素或逐块的鉴定方式耗时冗长。提出一种利用SIFT(尺度不变特征转换)特征的非对称搜索的复制粘贴伪造图像盲检测算法,算法利用图像SIFT特征初步定位复制粘贴伪造疑似区域,利用非对称特征搜索方式进行方向性的特征匹配,准确定位复制粘贴伪造区域。实验结果表明,本文算法能够准确检测复制粘贴伪造区域,检测结果不受高斯、椒盐等噪声的影响,检测效率比传统算法提高了1~2个数量级。

关 键 词:SIFT特征  非对称匹配  图像伪造  图像拼接  盲检测
收稿时间:9/4/2012 12:00:00 AM
修稿时间:2012/12/21 0:00:00

Fogery image blind detection by asymemetric search based on SIFT
Du Zhenlong,Yang Fan,Li Xiaoli,Guo Yanwen and Shen Ganggang.Fogery image blind detection by asymemetric search based on SIFT[J].Journal of Image and Graphics,2013,18(4):442-890.
Authors:Du Zhenlong  Yang Fan  Li Xiaoli  Guo Yanwen and Shen Ganggang
Affiliation:College of Electronics and Information Engineering, Nanjing University of Technology, Nanjing 210009, China;College of Electronics and Information Engineering, Nanjing University of Technology, Nanjing 210009, China;College of Electronics and Information Engineering, Nanjing University of Technology, Nanjing 210009, China;State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing 210000, China;College of Electronics and Information Engineering, Nanjing University of Technology, Nanjing 210009, China
Abstract:The identification of copy-paste forgery image is to find the suspicious region via pixel-by-pixel or block-by-block match, the computation costs is very heavy. An efficient blind forgery image detection approach based on scale-inva- riant feature transform (SIFT)is proposed in the paper, which employs SIFT keypoints for positioning the initial suspicious forgery region. The asymmetric search is exploited for refining the suspicious region and determining the forgery area. Experiments demonstrate that the proposed algorithm could significantly decrease the number of candidate search block, accurately identify the copy-paste forgery region regardless of the existence of gauss, salt and pepper noise, and the computational cost is reduced by 1~2 orders of magnitude with compare to the conventional methods.
Keywords:scale-invariant feature transform  asymmetric match  copy-paste forgery  image splicing  blind detection
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《中国图象图形学报》浏览原始摘要信息
点击此处可从《中国图象图形学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号