• DocumentCode
    177927
  • 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
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    1496
  • Lastpage
    1501
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.266
  • Filename
    6976976