| 基于数学形态学和神经网络对番茄生理病害果的识别 |
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| 引用本文： | 王艳平,戴小鹏,黄璜,张熔.基于数学形态学和神经网络对番茄生理病害果的识别[J].湖南农业大学学报(自然科学版),2006,32(3):344-346. |
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| 作者姓名： | 王艳平 戴小鹏 黄璜 张熔 |
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| 作者单位： | 1. 湖南农业大学农学院,湖南,长沙,410128
2. 湖南农业大学计算机与信息工程学院,湖南,长沙,410128 |
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| 基金项目： | 国家科技攻关项目;湖南农业大学校科研和教改项目 |
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| 摘 要： | 应用数学形态学理论，提出一种膨胀和腐蚀的快速算法运用于番茄不同病害果特征提取，运用计算机视觉技术，根据病害果的几何矩特征，应用神经网络技术进行番茄病害果识别．研究表明，该方法能准确识别番茄病害果的形状，满足分级的要求，识别率达90％以上．
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| 关 键 词： | 番茄生理病害果 计算机视觉技术 数学形态学 神经网络 矩特征 |
| 文章编号： | 1007-1032(2006)03-0344-03 |
| 修稿时间： | 2005年11月7日 |
Identification of Tomatoes with Diseases Based on Mathematical Morphology and Neural Network |
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| WANG Yan-ping,DAI Xiao-peng,HUANG Huang,ZHANG Rong.Identification of Tomatoes with Diseases Based on Mathematical Morphology and Neural Network[J].Journal of Hunan Agricultural University,2006,32(3):344-346. |
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| Authors: | WANG Yan-ping DAI Xiao-peng HUANG Huang ZHANG Rong |
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| Abstract: | A fast algorithm about dilation and erosion,based on mathematical morphology,was offered to extract features of different diseases,according to their quardrature characteristics.Computer vision technology and neural networks were applied to the identification of diseases.The results indicated that the method could accurately identify shapes and meet the requirement of classification,its accuracy ratio of recognizing tomates with diseases reached 90%. |
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| Keywords: | tomato with disease computer vision technology mathematical morphology neural network quadrature feature |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
