研究了可见光波段的黄瓜霜霉病信息分布和分割方法,有效实现了温室非结构环境下黄瓜病害信息识别.通过研究温室黄瓜图像在RGB、HIS和YCbCr颜色空间的分布特点,建立了光照分析模型,提高了不同光照条件下的病害提取适应性.分析了病害目标与环境背景Cb和Cr均值差,提出了CbCr组合算法,实现了目标的快速有效识别,满足了实时对靶施药的要求.通过随机抽取30幅黄瓜霜霉病图像进行算法验证,结果表明图像的平均识别正确率达90.6%.%An extraction algorithm based on color and texture was developed to realize segmentation between downy mildew and cucumber plants in greenhouse. A light analysis model was established by comparing the distribution of cucumber images in RGB, HIS and YCbCr color space, which was beneficial to the recognition of disease in variable illuminations. Combination model of Cb and Cr elements was built based on the mean difference of lesions and interference informations in Cb and Cr, which included leaves, poles and soil, and extracted target rapidly. A detecting expriment was carried out on 30 images with downy mildew, which were taken in a changing greenhouse enviornment. The results indicated that the accuracy rate of segmentation was 90. 6% .
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