Paper
5 August 2010 A passive scheme for tampering detection based on quantization table estimation
Guo-Shiang Lin, Min-Kuan Chang
Author Affiliations +
Proceedings Volume 7744, Visual Communications and Image Processing 2010; 774433 (2010) https://doi.org/10.1117/12.863502
Event: Visual Communications and Image Processing 2010, 2010, Huangshan, China
Abstract
In this paper, we proposed a passive scheme to achieve image tampering detection. To correctly estimate the quantization table, each AC DCT coefficient is classified into different types and then the corresponding quantization stepsize is adaptively measured from its power spectrum density (PSD) and PSD's Fourier transform. Based on the quantization table estimation, the proposed scheme is composed of pre-screening, candidate region selection, and tampering region identification. The pre-screening is developed to decide whether an image had been JPEG compressed. To select candidate regions for estimating quantization table, a seed region is first selected by finding a suitable region by removing suspicious regions. Based on the seed region, the candidate region can be obtained by suitably merging other regions into the seed. To avoid merging the suspect regions, a candidate region refinement is performed in the region growing. After estimating the quantization table from the candidate region, a MLR classifier based on the inconsistency of quantization table is exploited to identify tampered regions block by block. The experimental results demonstrate that our proposed scheme can not only estimate the quantization table but also identify tampered regions well.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guo-Shiang Lin and Min-Kuan Chang "A passive scheme for tampering detection based on quantization table estimation", Proc. SPIE 7744, Visual Communications and Image Processing 2010, 774433 (5 August 2010); https://doi.org/10.1117/12.863502
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Cited by 2 scholarly publications.
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KEYWORDS
Quantization

Image compression

Image quality

Digital watermarking

Digital imaging

Image analysis

Image processing

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