Abstract
Growing Self Organized Map (GSOM) algorithm is a well-known unsupervised clustering algorithm which a definite advantage is that both the map structure as well as the number of classes are automatically adjusted depending on the training data. We propose a new approach to apply it in the process of the image indexation and retrieval in a database. Unlike the classic bag-of-words (BoW) algorithm with k-means clustering, it is completely unnecessary to predetermine the number of classes (words). Thanks to that, the process of indexation can be fully automated. What is more, numerous modifications of the classic algorithm were added, and as a result, the retrieval process was considerably improved. Results of the experiments as well as comparison with BoW are presented at the end of the paper.
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Gabryel, M., Grycuk, R., Korytkowski, M., Holotyak, T. (2015). Image Indexing and Retrieval Using GSOM Algorithm. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_63
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DOI: https://doi.org/10.1007/978-3-319-19324-3_63
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