Paper
19 June 2017 Blind technique using blocking artifacts and entropy of histograms for image tampering detection
Manu V. T., B. M. Mehtre
Author Affiliations +
Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104430T (2017) https://doi.org/10.1117/12.2280306
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore
Abstract
The tremendous technological advancements in recent times has enabled people to create, edit and circulate images easily than ever before. As a result of this, ensuring the integrity and authenticity of the images has become challenging. Malicious editing of images to deceive the viewer is referred to as image tampering. A widely used image tampering technique is image splicing or compositing, in which regions from different images are copied and pasted. In this paper, we propose a tamper detection method utilizing the blocking and blur artifacts which are the footprints of splicing. The classification of images as tampered or not, is done based on the standard deviations of the entropy histograms and block discrete cosine transformations. We can detect the exact boundaries of the tampered area in the image, if the image is classified as tampered. Experimental results on publicly available image tampering datasets show that the proposed method outperforms the existing methods in terms of accuracy.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manu V. T. and B. M. Mehtre "Blind technique using blocking artifacts and entropy of histograms for image tampering detection", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430T (19 June 2017); https://doi.org/10.1117/12.2280306
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Cited by 1 scholarly publication.
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KEYWORDS
Chromium

Image classification

Transform theory

Raster graphics

Binary data

Digital watermarking

Feature extraction

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