Abstract
This paper presents a novel approach to detect and classify stamp instances in scanned documents. It incorporates several methods from the field of image processing, pattern recognition as well as some heuristic. At first, color separation is applied in order to find potential stamps. Next, several methods aimed at detecting objects of specific shapes are employed. Then, isolated objects are extracted and classified using a set of shape descriptors. Selected features are rotation, scale and translation invariant, hence this approach does not depend on the document size and orientation. The experiments performed on a large set of real documents retrieved from the Internet gave encouraging results.
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Forczmański, P., Markiewicz, A. (2013). Low-Level Image Features for Stamps Detection and Classification. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_37
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DOI: https://doi.org/10.1007/978-3-319-00969-8_37
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