With the increasing number of images generated every day, textual annotation of images becomes impractical and inefficient. Thus, content-based image retrieval (CBIR) has received considerable interest in recent years. Keeping it as the primary motivational focus, we propose a method which exploits different degrees of convexity of an object’s contour using a multi-level tree structured representation called Hierarchical Convex Polygonal Decomposition (HCPD) tree and the method also uses a special spiral-chain-code to encode the polygonal representation of decomposed shape at every node. The performance of the proposed scheme is reasonably good and comparable with existing state-of-the-art algorithms.
CITATION STYLE
Saha, S., Basak, J., & Mahapatra, P. R. S. (2015). A hierarchical convex polygonal decomposition framework for automated shape retrieval. In Advances in Intelligent Systems and Computing (Vol. 339, pp. 783–792). Springer Verlag. https://doi.org/10.1007/978-81-322-2250-7_78
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