基于最优颜色通道的图像拼接检测  

Image Splicing Detection Based on Optimal Color Channel

作　　者：熊士婷 张玉金 刘婷婷 方翔宇 XIONG Shiting;ZHANG Yujin;LIU Tingting;FANG Xiangyu(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620

出　　处：《电子科技》2020年第12期49-53,共5页Electronic Science and Technology

基　　金：上海市自然科学基金(17ZR1411900);上海工程技术大学研究生创新项目(18KY0208)。

摘　　要：针对不同颜色通道影响噪声估计值的问题,文中提出了基于最优颜色通道的图像拼接检测方法。利用主成分分析法在最优颜色通道上进行噪声值估计,根据噪声值大小利用K-means聚类法进行聚类。聚类结果分为可疑部分和非可疑部分两大类,通过两阶段策略进一步定位出篡改区域。该方法在原始区域与拼接区域噪声值相差较大或较小时均有效,并且能够定位出拼接区域。实验证明,所提方法与现有方法相比取得了良好的检测效果,且性能优于现有方法。In view of the problem that different color channels have effect on the noise estimation value,an image splicing detection method based on optimal color channel is proposed.The noise on the optimal color channel is estimated by principal component analysis and the method of K-means clustering is used to cluster according to the noise value.The clustering result is divided into suspicious part and non-suspicious part.The two-phase strategy can further locate the tampering area.The method is effective when the noise value difference between the original area and the splicing area was large or small,and the splicing area can be located.Experiments show that compared with the existing methods,the proposed method achieves good detection results,and the performance is better.

关 键 词：图像拼接检测 主成分分析 最优颜色通道 K-MEANS 拼接定位 噪声估计 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]