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作 者:岑喆鑫[1] 李宝聚[1] 石延霞[1] 黄海洋[2] 刘君[2] 廖宁放[3] 冯洁[3]
机构地区:[1]中国农业科学院菜蔬花卉研究所,北京100081 [2]北京师范大学数学科学学院,北京100875 [3]北京理工大学颜色科学与工程国家重点实验室,北京100081
出 处:《园艺学报》2007年第6期1425-1430,共6页Acta Horticulturae Sinica
基 金:国家‘863’项目(2006AA10Z210);国家自然科学基金项目(60678052);科研院所社会公益研究专项(2004DIB4J153);农业部蔬菜遗传与生理重点开放实验室项目
摘 要:为了进行数字化、标准化、无损伤定量识别植物病害,运用数字图像分析技术,对生产中两种常见的黄瓜病害(黄瓜炭疽病和黄瓜褐斑病)进行研究。利用图像的颜色统计特征对来自不同时期的病害样本图像进行分类和识别。采用逐步判别分析,选取显著性较大的特征参量,建立起黄瓜炭疽病、黄瓜褐斑病和无病区域的分类器模型。结果表明,对黄瓜炭疽病、黄瓜褐斑病和无病区域的正确回判率分别达到96.67%,93.33%和100%。测试集中,黄瓜炭疽病、黄瓜褐斑病和无病区域的正确识别率分别达到83.33%,80.00%和100%,说明利用彩色图像颜色统计特征对植物病害进行识别有可行性。In order to carrying on a digital, normalize, quantitative and undestroied method for plant disease discriminating, two kinds of familiar cucumber diseases (cucumber anthracnose and cucumber brown speck) were researched in the method of picture processing. Color characteristic parameters coming from different periods of disease simple were used to classification and identification. Using stepwise discriminant analysis to select significant parameters, and the bayesian classifier method was proposed to classify cucumber anthracnose, cucumber brown spot and healthy region. The result shows that the correct discrimination of cucumber anthracnose, cucumber brown spot and healthy region were 96. 67%, 93.33% and 100%, respectively. For the test set, the correct discrimination of cucumber anthracnose, cucumber brown spot and healthy region were 83.33%, 80. 00% and 100%, respectively. The results show that it is feasible to identify and classify plant diseases using color image statistical characteristics.
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