A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Leaf Image Retrieval with Shape Features
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
mCLOVER: mobile content-based leaf image retrieval system
Proceedings of the 13th annual ACM international conference on Multimedia
A shape-based retrieval scheme for leaf images
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Matching shapes with self-intersections: application to leaf classification
IEEE Transactions on Image Processing
A content based image retrieval system for a biological specimen collection
Computer Vision and Image Understanding
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Most content-based image retrieval systems use image features such as textures, colors, and shapes. However, in the case of leaf image, it is not appropriate to rely on color or texture features only because such features are similar in most leaves. In this paper, we propose a novel leaf image retrieval scheme which first analyzes leaf venation for leaf categorization and then extracts and utilizes shape feature to find similar ones from the categorized group in the database. The venation of a leaf corresponds to the blood vessel of organisms. Leaf venations are represented using points selected by the curvature scale scope corner detection method on the venation image, and categorized by calculating the density of feature points using non-parametric estimation density. We show its effectiveness by performing several experiments on the prototype system.