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Nonintrusive Image Tamper Detection Based on Fuzzy Fusion


Girija Chetty, Monica Singh


Vol. 10  No. 9  pp. 86-90


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.


image tampering, digital forensics, feature selection, fuzzy fusion