Detect Tampered Image: A New Approach

Abstract:

Detecting tampered image is a challenging work due to the high volume of image database and the accurate definition of tampering. We propose a novel algorithm based on standard deviation which could detect the tampered automatically, furthermore, localization and extraction process is conducted to optimize the proposed method. Color reduction technique, intensity based method for edge detection and horizontal based localization approach are applied here to fulfill the algorithm. The core idea of the paper is that normally tampered regions process high standard deviation while compared with non-tampered areas. As the result, the output of our algorithm is tampered regions. By presenting promising experience, the performance of proposed method is analyzed. Further application and possible optimization are discussed.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 3869-3874
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.3869
• Online since: November 2014
• Authors: Ting Wang*
• Keywords: Image Indexing, Standard Deviation, Tampered Images, Unsupervised Learning

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