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Anti-Forensics for Unsharp Masking Sharpening in Digital Images

Lu Laijie, Yang Gaobo and Xia Ming
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Lu Laijie: School of Information Science and Engineering, Hunan University, Changsha, China
Yang Gaobo: School of Information Science and Engineering, Hunan University, Changsha, China
Xia Ming: School of Information Science and Engineering, Hunan University, Changsha, China, & College of Electrical & Information Engineering, Southwest University for Nationalities, Chengdu, China

International Journal of Digital Crime and Forensics (IJDCF), 2013, vol. 5, issue 3, 53-65

Abstract: As a retouching tool, image sharpening can be applied as the final step to hide those possible forgery operations in an image. Unsharp masking (USM) is a popular sharpening method supported by most image editing software such as Adobe Photoshop. Several passive forensics methods have been presented for the detection of USM Sharpening. In this paper, an anti-forensic scheme for USM Sharpening is proposed to invalidate the existing forensic algorithms. It removes the overshoot artifacts in image edges and abrupt change in histogram ends. The effectiveness of the proposed method is proved by the experimental results on a large image database with various parameter settings. Comparisons are made among the unsharpened images, the sharpened images and the anti-forensic dithered image. Both the detection ability and image quality are used for its performance evaluation.

Date: 2013
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