Sawtooth feature extraction of leaf edge based on support vector machine

Abstract

The focus of Computer-Aided Plant-Identification (CAPI) is the stable features extraction of plant, such as sawtooth number of leaf edge for some species of plants. Because the shape of the sawteeth varies greatly, they cannot be depicted in rigid mathematic method. However, a trained SVM (Support Vector Machine) with good adaptability can be applied to classify sawtooth and nonsawtooth samples. The samples can be obtained by a rectangular sample window sliding along the edge of the leaf, and then be rotated to a standard pose for decreasing the complexity of identification. By avoiding repeated sampling and counting of the same sawtooth, the algorithm presented in the paper accomplishes automatic counting of the sawtooth number. The results of the experiment show that the SVM-based method works well.