关键词: 方向梯度直方图（HOG）特征, 支持向量机, 识别, 均值漂移算法, 定位, 检测

Abstract: For the purpose of automatic surveillance on wine grape in some aspects such as growth state, disease and insect pests, grape leaves should firstly be detected in an image. In this paper, a method is proposed in which Histogram of Oriented Gradient（HOG） features of a leaf are extracted and a classifier trained by support vector machine is used to identify the grape leaves in the images. The locations of the leaves in the image are determined by multi-scale object localization and mean shift algorithm. The experiment results show that the recognition rate of grape leaves and four common weed leaves reaches 95.5% when using the classifier trained with linear kernel function. The proposed method is robust to variety of illumination and environment. The detection rate of grape leaves of the images under natural conditions is over 80% in experiment.

Key words: Histogram of Oriented Gradient（HOG）, support vector machine, recognition, mean shift algorithm, location, detection