Image recapture detection using multiple features

被引：3

作者：

机构：

[1] School of Computer Science and Software Engineering, Tianjin Polytechnic University

[2] Department of Logistics Management, Nankai University

来源：

Qin, F. (fannq@163.com) | 2013年 / Science and Engineering Research Support Society, 20 Virginia Court, Sandy Bay, Tasmania, Australia卷 / 08期

关键词：

Color; Image Forensics; Image recapture detection; Noise; SVM; Texture;

D O I：

10.14257/ijmue.2013.8.5.08

中图分类号：

学科分类号：

摘要：

With advances in image display technology, recapturing good-quality images from high-fidelity artificial scenery on a LCD screen becomes possible. Forgers can recapture the artificially generated scenery and use the recaptured image to fool image forensic system. Image recapture detection is to distinguish real-scene images from the recaptured ones. An image recapture detection method based on multiple feature descriptors is proposed in this paper, which uses combinations of low-level features including texture, noise, difference histogram and color information. One hundred and thirty-six dimensions of features are extracted to train a support vector machine classifier with RBF kernel. Experimental results show that the proposed method is efficient with good detection rate of distinguishing real-scene images from the recaptured ones. It also possesses low dimensional features and low time complexity. © 2013 SERSC.

引用

页码：71 / 81

页数：10

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