Application of Principal Components Analysis and Gaussian Mixture Models to Printer Identification

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Abstract:

Printer identification based on a printed document has many desirable forensic applications. In the electrophotographic process (EP) quasiperiodic banding artifacts can be used as an effective intrinsic signature. However, in text only document analysis, the absence of large midtone areas makes it difficult to capture suitable signals for banding detection. Frequency domain analysis based on the projection signals of individual characters does not provide enough resolution for proper printer identification. Advanced pattern recognition techniques and knowledge about the print mechanism can help us to device an appropriate method to detect these signatures. We can get reliable intrinsic signatures from multiple projections to build a classifier to identify the printer. Projections from individual characters can be viewed as a high dimensional data set. In order to create a highly effective pattern recognition tool, this high dimensional projection data has to be represented in a low dimensional space. The dimension reduction can be performed by some well known pattern recognition techniques. Then a classifier can be built based on the reduced dimension data set. A popular choice is the Gaussian Mixture Model where each printer can be represented by a Gaussian distribution. The distributions of all the printers help us to determine the mixing coefficient for the projection from an unknown printer. Finally, the decision making algorithm can vote for the correct printer. In this paper we will describe different classification algorithms to identify an unknown printer. We will present the experiments based on several different EP printers in our printer bank. The classification results based on different classifiers will be compared.

Document Type: Research Article

Publication date: January 1, 2004

More about this publication?
  • For more than 25 years, NIP has been the leading forum for discussion of advances and new directions in non-impact and digital printing technologies. A comprehensive, industry-wide conference, this meeting includes all aspects of the hardware, materials, software, images, and applications associated with digital printing systems, including drop-on-demand ink jet, wide format ink jet, desktop and continuous ink jet, toner-based electrophotographic printers, production digital printing systems, and thermal printing systems, as well as the engineering capability, optimization, and science involved in these fields.

    Since 2005, NIP has been held in conjunction with the Digital Fabrication Conference.
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