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Mathematical Problems in Engineering
Volume 2015, Article ID 367879, 15 pages
Research Article

Stamps Detection and Classification Using Simple Features Ensemble

Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Żołnierska Street 52, 71-210 Szczecin, Poland

Received 1 August 2014; Accepted 23 September 2014

Academic Editor: Erik Cuevas

Copyright © 2015 Paweł Forczmański and Andrzej Markiewicz. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The paper addresses a problem of detection and classification of rubber stamp instances in scanned documents. A variety of methods from the field of image processing, pattern recognition, and some heuristic are utilized. Presented method works on typical stamps of different colors and shapes. For color images, color space transformation is applied in order to find potential color stamps. Monochrome stamps are detected through shape specific algorithms. Following feature extraction stage, identified candidates are subjected to classification task using a set of shape descriptors. Selected elementary properties form an ensemble of features which is rotation, scale, and translation invariant; hence this approach is document size and orientation independent. We perform two-tier classification in order to discriminate between stamps and no-stamps and then classify stamps in terms of their shape. The experiments carried out on a considerable set of real documents gathered from the Internet showed high potential of the proposed method.