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| 基于计算机视觉的番茄营养元素亏缺的识别 | |
| 引用本文： | 毛罕平,徐贵力,李萍萍. 基于计算机视觉的番茄营养元素亏缺的识别[J]. 农业机械学报, 2003, 34(2): 73-75 |
| 作者姓名： | 毛罕平 徐贵力 李萍萍 |
| 作者单位： | 1. 江苏大学研究生部,212013,镇江市 2. 南京航空航天大学测试工程系,210016,南京市 3. 江苏大学机械工程学院 |
| 基金项目： | 国家自然科学基金资助项目 (项目编号 :3 0 2 70 774)，江苏省自然科学基金资助项目 (项目编号 :BK2 0 0 10 89) |
| 摘 要： | 以肉眼不易识别的番茄缺氮和缺钾初期为研究对象，对体现在叶片颜色和纹理上的缺素症状进行了特征提取，利用遗传算法对提取的众多缺素特征进行优化组合，选择出用于模式识别分类器设计的特征向量，建立了二叉树分类法对番茄缺素进行模式识别的框架，在该框架下，基于模糊K－近邻法建立了缺素的模式识别系统，并进行了识别测试。结果表明，对不易肉眼判别的番茄缺氮和缺钾初期叶片的识别准确度在85％以上，能够满足生产要求。 |
| 关 键 词： | 农业机械 番茄 识别 计算机视觉 营养元素亏缺 |
| 修稿时间： | 2002-01-21 |
Diagnosis of Nutrient Deficiency of Tomato Based on Computer Vision |
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| Mao Hanping Li Pingping. Diagnosis of Nutrient Deficiency of Tomato Based on Computer Vision[J]. Transactions of the Chinese Society for Agricultural Machinery, 2003, 34(2): 73-75 | |
| Authors: | Mao Hanping Li Pingping |
| Affiliation: | Mao Hanping Li Pingping(Jiangsu University) Xu Guili(Nanjing University of Aeronautics and Astronautics) |
| Abstract: | The characteristic features of nitrogen and kalium deficiencies for tomatoes, which is hardly to be recognized in the initial period of growing, mainly represents on the color and texture of tomato leaves. The extraction of these nutrient deficiency features was made and the extracted features were optimized and combined to pick the eigenvectors out for the design of a mode identifying assorter. A mode identifying frame for deficient elements was set up by the tree taxonomy with two branches and then a mode identifying system was established based on the K neighbour approach. The results of the mode identify showed that the accuracy of the diagnosis reached about 85% before the symptoms could be recognized by eye. |
| Keywords: | Agricultural machinery Tomatoes Recognition Computer vision Nutrient deficiency |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |