| 基于遗传算法的番茄缺素叶片图像特征选择 |
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| 引用本文： | 徐贵力,程月华,毛罕平.基于遗传算法的番茄缺素叶片图像特征选择[J].计算机工程,2003,29(11):129-131. |
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| 作者姓名： | 徐贵力 程月华 毛罕平 |
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| 作者单位： | 1. 南京航空航天大学自动化学院,南京,210016
2. 江苏大学机械工程学院,镇江,212013 |
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| 基金项目： | 江苏省自然科学基金资助项目(BK2001089) |
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| 摘 要： | 在基于计算机视觉技术对无土栽培番茄营养元素缺乏智能识别研究中，如何选择出对缺素叶片分类能力强的特征项组合是识别诊断面临的关键问题，文章利用遗传算法对提取的缺素叶片图像众多颜色和纹理特征项进行优化选择，以达到诊断识别用的信息最优，实验表明，经过优化的特征组合明显优于人工选择的特征组合分类能力。
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| 关 键 词： | 特征项的选择 遗传算法 番茄 叶片 图像 |
| 文章编号： | 1000-3428(2003)11-0129-03 |
| 修稿时间： | 2002年6月4日 |
Features Selection of Leaves Image for Diagnosing Tomato Disease of Nutrient Deficiency Based on Genetic Algorithm |
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| XU Guili,CHENG Yuehua,MAO Hanping.Features Selection of Leaves Image for Diagnosing Tomato Disease of Nutrient Deficiency Based on Genetic Algorithm[J].Computer Engineering,2003,29(11):129-131. |
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| Authors: | XU Guili CHENG Yuehua MAO Hanping |
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| Affiliation: | XU Guili1,CHENG Yuehua1,MAO Hanping2 |
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| Abstract: | In the research of diagnosing tomato disease of nutrient deficiency intellectively in the soiless agriculture, feature selection is a key question in pattern recognition and affects the design and performance of the classifier. In this paper, using genetic algorithm (GA) to select features of leaves image is studied in order to get best information for diagnosing. The experimental res ults show that the effectiveness of features selected by GA is much better than the effectiveness of features selected by human. |
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| Keywords: | Feature selection Genetic algorithm Tomato Leaf Image |
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