Abstract
When very large image families are involved in query processes, methods of content-based image retrieval must be optimized with a goal function determining a computing complexity. A clustering method which at the image retrieval stage ensure minimal number of comparisons of a query image and images from image database is proposed. Clustering can be fulfilled in feature or signal space. Pointwise set maps are used as the tools to find required partitions.
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Kinoshenko, D., Mashtalir, V., Yegorova, E. (2006). CLUSTERING METHOD FOR FAST CONTENTBASED IMAGE RETRIEVAL. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_138
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DOI: https://doi.org/10.1007/1-4020-4179-9_138
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-4178-5
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