Abstract
In this paper, we propose an extraction method of optimal interest points to support shape-based image classification and indexing for image database by applying a dynamic threshold that reflects the characteristics of a shape contour. The threshold is dynamically determined by comparing the contour length ratio of the original shape and the approximated polygon while the algorithm is running. Because our algorithm considers the characteristics of the shape contour, it can minimize the number of interest points. For a shape with n contour points, this algorithm has the time complexity O(n logn). Our experiments show the average optimization ratio up to 0.92. We expect that features of shapes extracted from the proposed method are used for shape-based image classification, indexing, and similarity search.
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Um, K., Jo, S., Cho, K. (2006). An Extraction Technique of Optimal Interest Points for Shape-Based Image Classification. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_67
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DOI: https://doi.org/10.1007/11848035_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
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