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基于灰度共生矩的图像区域复制篡改检测
引用本文:欧佳佳,蔡碧野,熊兵,李峰.基于灰度共生矩的图像区域复制篡改检测[J].计算机应用,2011,31(6):1628-1630.
作者姓名:欧佳佳  蔡碧野  熊兵  李峰
作者单位:长沙理工大学 计算机与通信工程学院,长沙 410114
基金项目:国家自然科学基金资助项目,湖南省自然科学基金资助项目,湖南省教育厅科学研究项目
摘    要:针对图像区域复制—粘贴篡改,提出了一种基于灰度共生矩阵的检测算法。首先将待检测图像分成大小相同的多个重叠块,用灰度共生矩阵的统计量表示每块图像的纹理特征,得到图像的特征矢量。然后将特征矢量进行字典排序,并结合图像块的位移矢量,检测且定位出篡改区域。实验结果表明,该算法在抗旋转处理和效率方面均优于经典的基于主成分分析法(PCA)的检测算法。

关 键 词:数字图像取证    图像区域复制粘贴篡改    灰度共生矩阵
收稿时间:2010-12-14
修稿时间:2011-01-17

Detection of image region-duplication forgery based on gray level co-occurrence matrix
OU Jia-jia,CAI Bi-ye,XIONG Bing,LI Feng.Detection of image region-duplication forgery based on gray level co-occurrence matrix[J].journal of Computer Applications,2011,31(6):1628-1630.
Authors:OU Jia-jia  CAI Bi-ye  XIONG Bing  LI Feng
Affiliation:College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha Hunan 410114, China
Abstract:With regard to the copy-move forgery of image region, this paper proposes a detection algorithm based on gray level co-occurrence matrix. Firstly, we divided the detected image into multiple overlapping blocks with same sizes, represented the textural features of each block with the statistics of its gray level co-occurrence matrix, and got the feature vector of the image. Secondly, we sorted the feature vector by dictionary, and located the tampered region by utilizing the displacement vectors of image blocks. Lastly, experimental results show that our algorithm performs better than the classical detection algorithm based on Principal Component Analysis (PCA) in terms of the processing against rotate operation and of efficiency.
Keywords:digital image forensics                                                                                                                          image region copy-move tampering                                                                                                                          gray level co-occurrence matrix
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