Image Tamper Blind Detection Based on CFA

Dong Sheng Ji; Rui Yang Yang; Ting Cao; Yu Kai Yao; Xiao Yun Chen

doi:10.4028/www.scientific.net/AMM.496-500.2237

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 496-500Image Tamper Blind Detection Based on CFA

Image Tamper Blind Detection Based on CFA

Abstract:

Most of the methods need to build a sophisticated classifier to detect the image tamper which leads the lower detection efficiency. For this problem, we propose a method based on artifacts detection techniques in the process produces of CFA, which includes one based on CFA pattern number estimation and the other noise analysis based on CFA. The techniques are based on computing a single feature and a simple threshold based on classifier, determine whether the mosaic artifacts of the CFA was changed. The experimental results show that, the proposed approach has higher performance.

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Periodical:

Applied Mechanics and Materials (Volumes 496-500)

Pages:

2237-2240

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.496-500.2237

Citation:

Cite this paper

Online since:

January 2014

Authors:

Dong Sheng Ji, Rui Yang Yang, Ting Cao, Yu Kai Yao, Xiao Yun Chen

Keywords:

CFA, Demosaicing Operation, Digital Image Forensics, Noise Analysis, Tamper Detection

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