In this paper we present an efficient two-step approach of using a shape characterization function called centroid-contour distance curve and the object eccentricity (or elongation) for leaf image retrieval. Both the centroid-contour distance curve and the eccentricity of a leaf image are scale, rotation, and translation invariant after proper normalizations. In the frist step, the eccentricity is used to rank leaf images, and the top scored images are further ranked using the centroid-contour distance curve together with the eccentricity in the second step. A thinningbased method is used to locate start point(s) for reducing the matching time. Experimental results show that our approach can achieve good performance with a reasonable computational complexity.
CITATION STYLE
Wang, Z., Chi, Z., Feng, D., & Wang, Q. (2000). Leaf image retrieval with shape features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1929, pp. 477–487). Springer Verlag. https://doi.org/10.1007/3-540-40053-2_42
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