关键词: 烟叶病害, 图像处理, 模糊模式识别, 标准特征库, 模糊C均值聚类算法

Abstract: To overcome the shortage of inaccuracies and subjectivity in disease artificial recognition of tobacco leaf, a fast classification algorithm based on computer image processing technology is presented for tobacco brown spot and tobacco wildfire disease in this paper. The algorithm mainly includes two parts of feature parameters extraction and disease classification. Through image analysis for these two tobacco leaf diseases, six feature parameters for disease recognition are given by optimum seek, and a standard feature library is established. Fuzzy pattern recognition algorithm based on standard feature library is used in tobacco leaf disease recognition and classification. Then, the method is compared with the fuzzy C-means clustering algorithm. The experimental results of tobacco brown spot and tobacco wildfire disease classification show that the proposed classification recognition algorithm has good rate of identification.

Key words: tobacco leaf diseases, image processing, fuzzy pattern recognition, standard feature library, fuzzy C-means clustering algorithm