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A Model-Based Approach for Compound Leaves Understanding and Identification

Abstract : In this paper, we propose a specific method for the identification of compound-leaved tree species, with the aim of integrating it in an educational smartphone application. Our work is based on dedicated shape models for compound leaves, designed to estimate the number and shape of leaflets. A deformable template approach is used to fit these models and produce a high-level interpretation of the image content. The resulting models are later used for the segmentation of leaves in both plain and natural background images, by the use of multiple region-based active contours. Combined with other botany-inspired descriptors accounting for the morphological properties of the leaves, we propose a classification method that makes a semantic interpretation possible. Results are presented over a set of more than 1000 images from 17 European tree species, and an integration in the existing mobile application Folia is considered.
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Contributor : Guillaume Cerutti <>
Submitted on : Monday, October 14, 2013 - 3:38:03 PM
Last modification on : Tuesday, November 19, 2019 - 2:41:34 AM
Document(s) archivé(s) le : Friday, April 7, 2017 - 10:50:08 AM


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  • HAL Id : hal-00872889, version 1


Guillaume Cerutti, Laure Tougne, Julien Mille, Antoine Vacavant, Didier Coquin. A Model-Based Approach for Compound Leaves Understanding and Identification. International Conference on Image Processing (ICIP), Sep 2013, Melbourne, Australia. pp.1471-1475. ⟨hal-00872889⟩



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