文章详细信息 关键词： 黄瓜病害;;图像处理;;数学建模;;高斯混合模型 [gap=559]Keywords: Cucumber disease;Image processing;Mathematical modeling;Gaussian Mixture Model
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gray mold disease of cucumber 胡瓜灰霉病
cucumber spot disease 黄瓜褐斑病
cucumber wilt disease 黄瓜枯萎病
cucumber mildew disease 黄瓜霜霉病
cucumber mosaic disease 黄瓜花叶病
Cucumber foliage disease 黄瓜叶面病害
cucumber seedling disease 黄瓜苗病
cucumber necrosis disease 黄瓜坏死病
cucumber wilt disease fungus 黄瓜枯萎病菌
Cucumber disease leaf was as an example in this paper and the major work is summarized below:1.
本文以黄瓜病害为例,主要工作总结如下:1.黄瓜病害图像预处理。
参考来源 - 基于图像识别的作物病害诊断研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The result showed that it was speedy to extract spectral feature of cucumber disease by the gray of images.
实验结果表明，用亮度信息提取霜霉病害的多光谱图像特征波段，能快速提取病害的特征波段信息。
The comparison of different kernel functions for SVM shows that liner kernel function is most suitable for recognition of cucumber disease.
不同分类核函数的相互比较分析表明，线性核函数最适合黄瓜病害识别。
At first, extracting features of chromaticity moments is done, then classification method of SVM for recognition of cucumber disease is discussed.
在进行分类时，首先以色度矩作为特征向量，然后将支持向量机分类方法应用于黄瓜病害的识别。
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