Leaf identification using apical and basal features

This paper proposes a method that extracts local features, i.e., angle patterns, around the apex and base of a leaf. The proposed method only requires leaf contour and the location of apex and base as inputs. Starting from an origin point, which can be either the apex or base, the contour is tracked in two directions, i.e., leftward and rightward, and then sampled at five different distances from the origin point. The angle formed by the origin and two sampled points, at each distance, is then calculated. Altogether, 10 angle features, five from the apex and five from the base, are obtained. These features are invariant to translation, rotation, and scaling. In addition, this paper also aims to measure the effectiveness of the proposed apical and basal features. In the experiment, two sets of features are compared. The first set includes 12 shape descriptors while the second set includes not only the 12 shape descriptors but also the proposed features. By using support vector machine as a classifier, leaf identification has been done by using the two sets of features. Experimental results indicate that the use of apical and basal features can significantly improve the accuracy of leaf identification.