An Image Forensics Algorithm for Blur Detection Based on Properties of Sharp Edge Points

摘要：

This paper proposes a algorithm for detecting manual blur on images, which is usually used to remove obvious traces when tamper images.The algorithm first blurs the test image and blocks the both test image and blurred image.Then extracts and compares the sharp edge points in contourlet domain of the two images, so as to detect the suspicious blurred blocks.Furthermore, differences between manual blur and defocus blur can be indicated by our proposed method, and we can find out whether the image has been manual blurred.We establish a rich set of experimental images, and test results show that the average accurate detection rate is high, and the tampered regions can be always located.Our next work is to improve the robustness of the algorithm.

关键词： forensics manual blur sharp edge point contourlet

作者: Ll-Xian WEI Junjie ZHU Xiaoyuan YANG

作者单位: Key Laboratory of Network & Information Security of Engineering College of the Armed Police Force Xi Key Laboratory of Network & Information Security of Engineering College of the Armed Police Force Xi

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Material and Manufacturing Technology(2011第二届材料与制造技术国际会议 ICMMT2011)

会议地点: 厦门

会议语种:英文

页码: 743-747

在线出版日期: 2011-07-08（万方平台首次上网日期，不代表论文的发表时间）