Title :
Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy
Author :
Liu, H. ; Coquin, D. ; Valet, L. ; Cerutti, G.
Author_Institution :
LISTIC, Univ. de Savoie, Annecy le Vieux, France
Abstract :
Within the framework of a smartphone-based application, helping people to identify plant species in the wild, a sub-classifier strategy has been introduced. It aims at recognizing the botanical properties of a leaf, relatively to various global and local shape criteria used in flora books. A decision function is applied on these classified shape categories to produce a final decision on the species of the leaf. In this paper, the fusion strategy and its corresponding Random-Forest-based sub-classifiers are described. The results of these algorithms for botanical leaf shape recognition demonstrate that our classification algorithm can achieve good performance on leaf species identification while providing the user with relevant information for educational purposes.
Keywords :
botany; image classification; image fusion; learning (artificial intelligence); smart phones; botanical leaf shape recognition; botanical shape subclassifier strategy; decision function; educational purposes; flora books; fusion strategy; global shape criteria; leaf botanical property recognition; leaf species classification; local shape criteria; plant species identification; random-forest-based subclassifiers; shape category classification; smart phone-based application; Decision trees; Feature extraction; Image recognition; Radio frequency; Shape; Training; Vegetation; Belief functions theory; Data Classification; Dempster-Shafer theory; Leaf recognition; Random Forest;
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
DOI :
10.1109/ICPR.2014.266