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DOI: 10.14569/IJACSA.2010.010603
PDF

Quantization Table Estimation in JPEG Images

Author 1: Salma Hamdy
Author 2: Haytham El-Messiry
Author 3: Mohamed Roushdy
Author 4: Essam Kahlifa

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 6, 2010.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

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.

Keywords: Digital image forensics; forgery detection; compression history; Quantization tables.

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

@article{Hamdy2010,
title = {Quantization Table Estimation in JPEG Images },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2010.010603},
url = {http://dx.doi.org/10.14569/IJACSA.2010.010603},
year = {2010},
publisher = {The Science and Information Organization},
volume = {1},
number = {6},
author = {Salma Hamdy and Haytham El-Messiry and Mohamed Roushdy and Essam Kahlifa}
}



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.

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