期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2010
卷号：10
期号：9
页码：86-90
出版社：International Journal of Computer Science and Network Security
摘要：In this paper, we propose a novel fuzzy fusion of image residue features for detecting tampering or forgery in video sequences. We suggest use of feature selection techniques in conjunction with fuzzy fusion approach to enhance the robustness of tamper detection methods. We examine different feature selection techniques, the independent component analysis (ICA), and the canonical correlation analysis (CCA) for achieving a more discriminate subspace for extracting tamper signatures from quantization and noise residue features. The evaluation of proposed fuzzy fusion technique along with different feature selection techniques for copy-move tampering emulated on low bandwidth Internet video sequences, show a significant improvement in tamper detection accuracy with fuzzy fusion.
关键词：image tampering; digital forensics; feature selection; fuzzy fusion
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