Plant identification using triangular representation based on salient points and margin points

Leaf classification is an important component of living plant identification. A leaf contains important information for plant species identification in spite of its complexity. This paper introduces a method of recognizing leaf images based on triangular representations. A leaf is represented by local descriptors associated with margin sample points and salient sample points. We introduce three new triangular representations - salient triangle area representation (STAR), salient triangle side lengths representation (STSL), and salient triangle area, side lengths and two angles representation (STASLA), and then we combine two local descriptors - one provides a triangular representation of the leaf margin while the other represents the spatial correlation between salient points of the leaf and leaf margin. Experiments on the Image-CLEF 2011 leaf datasets show the effectiveness and the efficiency of the proposed method.