Color laser printer identification by analyzing statistical features on discrete wavelet transform

Authors:
Jung-Ho Choi;Dong-Hyuck Im;Hae-Yeoun Lee;Jun-Taek Oh;Jin-Ho Ryu;Heung-Kyu Lee
Affiliations:
School of Electrical Engineering and Computer Science, KAIST, Korea Minting & Security Printing Corporation, Republic of Korea;School of Electrical Engineering and Computer Science, KAIST, Korea Minting & Security Printing Corporation, Republic of Korea;School of Computer and Software Engineering, Kumoh National Institute of Technology, Korea Minting & Security Printing Corporation, Republic of Korea;Information Technology Laboratory, Technology Research Institute, Korea Minting & Security Printing Corporation, Republic of Korea;Information Technology Laboratory, Technology Research Institute, Korea Minting & Security Printing Corporation, Republic of Korea;School of Electrical Engineering and Computer Science, KAIST, Korea Minting & Security Printing Corporation, Republic of Korea
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

Color laser printers are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. First, 39 noise features of color printed images are extracted from the statistical analysis of the HH sub-band on discrete wavelet transform. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, 9 models of 4 brands, Xerox, Konica, HP, Canon, are tested to classify the brand of color laser printer, the color toner, and the model of color laser printer. The results prove that the presented identification method performs well using the noise features of color printed images.