关键词: 烟草, 蛙眼病, 赤星病, 图像分割, 特征提取, 蚁群算法, 萤火虫算法, 支持向量机

Abstract: For the accurate identification of tobacco disease and providing scientific basis for formulating control methods.A recognition method based on(FA-SVM)technology was proposed.The tobacco brown spot and frog eye disease were selected as the research object.The leaves of tobacco plants with two diseases were photographed by visible light.The segmentation and morphology methods were used to acquire disease spot images.Thirty-two features of spot were extracted to construct the original feature space,including color features,morphological features and texture features.The ant colony optimization(ACO) algorithm was used to extract the partial features build of the optimal feature space by the fitness function.The thirteen features were determined and the max fitness value was 95.68.The firefly algorithm(FA) was used to optimize the penalty factor(c)and the kernel function parameter(g)of support vector machine(SVM).The recognition accuracy of the classification model reached 96% when c=94.12,g=2.43.The results showed that the identification of tobacco disease is feasible based on FA-SVM technology.

Key words: Tobacco, Frog eye disease, Brown spot, Image segmentation, Feature extraction, Ant colony optimization, Firefly algorithm, Support vector machine