Date of Award
12-2010
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Computer Science
Department
Computer Science
Major Professor
Roussev, Vassil
Second Advisor
Tu, Shengru
Third Advisor
Richard, Golden G.
Abstract
In digital forensics, source camera identification of digital images has drawn attention in recent years. An image does contain information of its camera and/or editing software somewhere in it. But the interest of this research is to find manufacturers (henceforth will be called make and model) of a camera using only the header information, such as quantization table and huffman table, of the JPEG encoding. Having done research on around 110, 000 images, we reached to state that "For all practical purposes, using quantization and huffman tables alone to predict a camera make and model isn't a viable approach". We found no correlation between quantization and huffman tables of images and makes of camera. Rather, quantization or huffman table is determined by the quality factors like resolution, RGB values, intensity etc.of an image and standard settings of the camera.
Recommended Citation
Tuladhar, Punnya, "Nonattribution Properties of JPEG Quantization Tables" (2010). University of New Orleans Theses and Dissertations. 1261.
https://scholarworks.uno.edu/td/1261
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.