Abstract
In this paper we propose a novel method of scene classification, based on the idea of mining emerging patterns between classes of images, represented in a symbolic manner. We use the 9DLT (Direction Lower Triangular) representation of images, which allows to describe scenes with a limited number of symbols, while still capturing spatial relationships between objects visible on the images. We show an efficient method of mining the proposed Spatial Emerging Patterns and present results of synthetic image classification experiments.
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Kobyliński, Ł., Walczak, K. (2010). Spatial Emerging Patterns for Scene Classification. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_64
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DOI: https://doi.org/10.1007/978-3-642-13208-7_64
Publisher Name: Springer, Berlin, Heidelberg
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