Leaf Classification Using Navigation-Based Skeletons

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.

Authors

• Georgios Sakellariou
• Murray Shanahan

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