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A Representation and Matching Method for Shape-based Leaf Image Retrieval  

Nam, Yun-Young (아주대학교 정보통신전문대학원)
Hwang, Een-Jun (고려대학교 전자컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.32, no.11, 2005 , pp. 1013-1020 More about this Journal
Abstract
This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.
Keywords
image retrieval; content-based retrieval; shape-based retrieval; image indexing; QBE(Query By Example); QBS(Query By Sketch);
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