| 基于遗传算法的玉米病害图像特征优化与识别 |
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| 引用本文： | 唐朝霞,张粤. 基于遗传算法的玉米病害图像特征优化与识别[J]. 安徽农业大学学报, 2013, 40(2): 336 |
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| 作者姓名： | 唐朝霞 张粤 |
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| 作者单位： | 淮阴工学院计算机工程学院,淮安 223003 |
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| 基金项目： | 江苏省科技型企业创新项目（BC2011441）资助。 |
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| 摘 要： | 以玉米病害图像为例,经图像预处理后,采用遗传算法从图像纹理、颜色和形状多个原始特征中优选,优化出相关信息测度、归一化蓝色颜色分量 b 值、Cb、颜色矩、病斑周长和形状因子等独立性、稳定性好及分类能力强的特征向量用于病害识别.利用SPSS软件提供的Bayes判别分析结果表明,该方法提高了病害图像识别的效率和精度.
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| 关 键 词： | 遗传算法 病害识别 特征优化 |
| 收稿时间： | 2012-11-02 |
Optimization and recognition of maize disease image features based on genetic algorithms |
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| TANG Zhao-xia and ZHANG Yue. Optimization and recognition of maize disease image features based on genetic algorithms[J]. Journal of Anhui Agricultural University, 2013, 40(2): 336 |
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| Authors: | TANG Zhao-xia and ZHANG Yue |
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| Affiliation: | Department of Computer Engineering, Huaiyin Institute of Technology, Huaian 223003 and Department of Computer Engineering, Huaiyin Institute of Technology, Huaian 223003 |
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| Abstract: | In this article, we took the pretreated maize disease images as example, and employed genetic algorithms to choose approximate and effective image features, including relevant information measure, color components b and Cb, color moments, lesion perimeter, shape factor etc as recognition features from many primordial features. The Bayes discriminant analysis results provided by SPSS software show that this method can improve the efficiency and accuracy of the disease image recognition. |
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| Keywords: | genetic algorithms disease recognition feature optimization |
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