Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2010.010603
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 6, 2010.
Abstract: Most digital image forgery detection techniques require the doubtful image to be uncompressed and in high quality. However, most image acquisition and editing tools use the JPEG standard for image compression. The histogram of Discrete Cosine Transform coefficients contains information on the compression parameters for JPEGs and previously compressed bitmaps. In this paper we present a straightforward method to estimate the quantization table from the peaks of the histogram of DCT coefficients. The estimated table is then used with two distortion measures to deem images as untouched or forged. Testing the procedure on a large set of images gave a reasonable average estimation accuracy of 80% that increases up to 88% with increasing quality factors. Forgery detection tests on four different types of tampering resulted in an average false negative rate of 7.95% and 4.35% for the two measures respectively.
Salma Hamdy, Haytham El-Messiry, Mohamed Roushdy and Essam Kahlifa, “Quantization Table Estimation in JPEG Images ” International Journal of Advanced Computer Science and Applications(IJACSA), 1(6), 2010. http://dx.doi.org/10.14569/IJACSA.2010.010603