H.: Participation of LSIS/DYNI to ImageCLEF 2012 plant images classification task. In: Working notes of CLEF 2012 conference

Abstract. This paper presents the participation of the LSIS/DYNI team for the ImageCLEF 2012 plant identification challenge. Image-CLEF’s plant identification task provides a testbed for the system-oriented evaluation of tree species identification based on leaf images. The goal is to investigate image retrieval approaches in the context of crowd sourced images of leaves collected in a collaborative manner. The LSIS/DYNI team submitted three runs to this task and obtained the best evalua-tion scores (S = 0.32) for the ”photograph ” image category with an automatic method. Our approach is based on a modern computer vi-sion framework involving local, highly discriminative visual descriptors, sophisticated visual-patches encoder and large-scale supervised classifi-cation. The paper presents the three procedures employed, and provides an analysis of the obtained evaluation results