Abstract
Image classification is very helpful for organizing large image databases and content based image retrieval (CBIR). However, it is very complex and challenging because of lacking effective methods. In this paper, we present a tree representation of images based on rectangular-shape partition. Then an adaptive processing algorithm is adopted to perform the classification task. Experimental results on seven categories of scenery images show that the structural representations are better than the traditional methods and our previous work based on quadtree representation of fixed partition.
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Sun, W., Lo, K., Chi, Z. (2005). Scene Classification Using Adaptive Processing of Tree Representation of Rectangular-Shape Partition of Images. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_44
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DOI: https://doi.org/10.1007/11427445_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
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