农业喷雾对象的识别和定位是农业自动化喷雾机械研究中的核心技术之一. 对病虫害甘蓝进行精准喷洒农药,实现病虫害准确自动识别成为关键. 为此,利用机器视觉的欧氏距离甘蓝夜蛾虫害自动识别检测系统,结合由Qualityspec 光谱仪组成的光谱成像系统,对甘蓝正常叶片和遭受甘蓝夜蛾虫害的甘蓝叶片的颜色特征和光谱特征进行分析,并采用机器视觉分割阈值选取中的Otsu算法和自适应波段选择方法提取出了颜色差异的最佳几何阈值和两种叶片的特征波段. 试验结果表明:综合机器视觉和光谱技术能够实现甘蓝夜蛾虫害的自动且准确的识别,准确率可达94%. 因此,建立机器视觉和光谱技术综合识别体系,可为农作物病虫害自动防治喷雾机器人的研制奠定基础,以达到农作物病虫害实时识别和及时治理的目的.%The spray object recognition and localization is one of the core technology of automatic spray mechanization re -search .For precision spraying pesticide plant diseases and insect pests of cabbage , the accurate and automatic identifica-tion of plant diseases and insect pests of cabbage becomes the key .Therefore , using machine vision automatic identifica-tion of the Euclidean distance of cabbage moth pests detection system , combined with spectral imaging system composed of qualityspec spectrometer , Cabbage normal blade and suffer from the cabbage moth pests of cabbage leaf color features and spectral characteristics were analyzed .The best geometric threshold of color difference and characteristic bands of two kinds of leaves were extracted , using the Otsu threshold value image segmentation algorithm and adaptive band selection method.The test results show that the technology compositing image processing with spectrum can realize automatic and accurate identification of Cabbage moth pests , accuracy reaching 94%.Therefore, the establishment of comprehensive image processing and spectroscopy identification system can lay the foundation for the development of the automatic con -trol of spray robot , in order to achieve the purpose of crop diseases and pests identification and real -time treatment .
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