Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reliable Classification of Chrysanthemum Leaves through Curvature Scale Space
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Fast Best-Match Shape Searching in Rotation-Invariant Metric Spaces
IEEE Transactions on Multimedia
Matching shapes with self-intersections: application to leaf classification
IEEE Transactions on Image Processing
Advanced shape context for plant species identification using leaf image retrieval
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
A sectorized object matching approach for breast magnetic resonance image similarity study
Proceedings of the 2012 ACM Research in Applied Computation Symposium
A shape-based approach for leaf classification using multiscaletriangular representation
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Proceedings of the 2013 Research in Adaptive and Convergent Systems
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In this paper, an effective shape-based leaf image retrieval system is presented. A new contour descriptor is defined which reduces the number of points for the shape representation considerably. This shape representation is based on the curvature of the leaf contour and it deals with the scale factor in a novel and compact way. A two-step algorithm for retrieval is used. In a first step, the database is reduced using some geometrical features. Then a similarity measure between the contour representations is used to rank conveniently leaf images on the database. We implemented a prototype system based on these features and performed several experiments to show its effectiveness for plant species identification.