ReVeS Participation - Tree Species Classification Using Random Forests and Botanical Features.

This paper summarizes the participation of the ReVeS project to the ImageCLEF 2012 Plant Identification task. Aiming to develop a system for tree leaf identification on mobile devices, our method is designed to cope with the challenges of complex natural images and to enable a didactic interaction with the user. The approach relies on a two step model-driven segmentation and on the evaluation of high-level characteristics that make a semantic interpretation possible, as well as more generic shape features. All these descriptors are combined in a random forest classification algorithm, and their significance evaluated. Our team ranks 4th overall, 3rd on natural images, which constitutes a very satisfying performance with respect to the project’s objectives.

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