Principles of artificial intelligence
Principles of artificial intelligence
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Shock Graphs and Shape Matching
International Journal of Computer Vision
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A hierarchy of boundary-based shape descriptors
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Supervaluation semantics for an inland water feature ontology
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Matching shapes with self-intersections: application to leaf classification
IEEE Transactions on Image Processing
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In this paper, we present a leaf classification method based on skeletons produced by a navigation-inspired technique. The classification system comprises three separate stages. First, a skeletonisation algorithm is used to gather low level structural and morphological information about the shape. Subsequently, the data is converted into a series of attributed graphs. Graphs of the same type are then compared using an approximate graph matcher, which identifies a degree of similarity between them. Each degree of similarity corresponds to a dimension in a conceptual space, as defined by Gärdenfors. We test the performance of our technique on a set of leaves belonging to three different species.