Abstract
Finding key points based on SURF and SIFT and size of their vector reduction is a classical approach for object recognition systems. In this paper we present a new framework for object recognition based on generating simple fuzzy classifiers using key points and boosting meta learning to distinguish between one known class and other classes. We tested proposed approach on a known image dataset.
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Gabryel, M., Korytkowski, M., Scherer, R., Rutkowski, L. (2013). Object Detection by Simple Fuzzy Classifiers Generated by Boosting. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_49
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DOI: https://doi.org/10.1007/978-3-642-38658-9_49
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