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Proceedings Paper

Classifying digital prints according to their production process using image analysis and artificial neural networks
Author(s): Jack Tchan
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Paper Abstract

A human expert observer can be employed to identify the production source of a print. The observer achieves this task by visual inspection of the print using a microscope. However, there are cases when the expert observer fails to identify correctly the production source. It is for this reason that the development of a method which can identify the production source is under consideration. This paper discusses the initial stages of the project which focuses on the development of a system that can classify prints from three different digital printing process. The system comprised an image analyzer that supplied image data from the print samples for initial analysis using a data pre- processing program and artificial neural networks which then used the pre-processed data to produce the classification models. The three different digital printing processes employed in this investigation were laser printing, optical photocopying and inkjet printing. Print samples were obtained from a range of laser printers,,optical photocopiers and inkjet printers. The prints used in the investigation were of a monochrome image of a square. The results show that the system is capable of classifying prints accurately for the range of printing machines and the image used in the trials.

Paper Details

Date Published: 7 April 2000
PDF: 12 pages
Proc. SPIE 3973, Optical Security and Counterfeit Deterrence Techniques III, (7 April 2000); doi: 10.1117/12.382180
Show Author Affiliations
Jack Tchan, London College of Printing (United Kingdom)


Published in SPIE Proceedings Vol. 3973:
Optical Security and Counterfeit Deterrence Techniques III
Rudolf L. van Renesse; Willem A. Vliegenthart, Editor(s)

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