Abstract
Retrieval of images based on the content is a process that requires the comparison of the multidimensional representation of the contents of a given example with all of those images in the database. To speed up this process, several indexing techniques have been proposed. All of them do efficiently the work up to 30 dimensions [8]. Above that, their performance is affected by the properties of the multidimensional space. Facing this problem, one alternative is to reduce the dimensions of the image representation which however conveys an additional loss of precision. Another approach that has been studied and seems to exhibit good performance is the clustering of the database. On this article we analyze this option from a computational complexity approach and devise a proposal for the number of clusters to obtain from the database, which can lead to sublinear algorithms.
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Manjarrez Sanchez, J.R., Martinez, J., Valduriez, P. (2007). On the Usage of Clustering for Content Based Image Retrieval. In: Diekert, V., Volkov, M.V., Voronkov, A. (eds) Computer Science – Theory and Applications. CSR 2007. Lecture Notes in Computer Science, vol 4649. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74510-5_29
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DOI: https://doi.org/10.1007/978-3-540-74510-5_29
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