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首页> 外文会议>IFIP WG 5.14 International conference on computer and computing technologies in agriculture >Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method
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Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

机译：基于HSV和OTSU方法的玉米病害颜色形状识别研究。

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With the application of IOT technology in maize disease images for monitoring and collecting, timely detection of the types and characteristics of identification of disease has become a hot research in the diagnosis and treatment of diseases and insect pests. In order to improve the recognition accuracy of maize leaf, achieve rapid diagnostic purposes, this paper takes the leaf spot of maize gray leaf spot and image as the research object, use the computer image processing technology is studied on the effective segmentation and recognition of color and shape features. The genetic algorithm was adopted to optimize the selection of maize disease images real-time filtering; 3*3 mode noise suppression of the image selected by value smoothing; then select the HSV component of the color feature extraction of the disease; the maximum between class variance (OTSU) disease shape character segmentation and recognition. The results show that, based on genetic algorithm optimization based on image In HSV and Otsu method can be more accurate segmentation and recognition of the disease of color and shape features, and enhance the real-time and accuracy of the image of maize disease detection and recognition and oriented under the condition of things plant diseases and insect pests of maize and provide technical support.
机译：随着物联网技术在玉米病害图像监测与采集中的应用，及时发现病害的种类和特征，已成为病虫害诊治领域的研究热点。为了提高玉米叶的识别精度，达到快速诊断的目的，本文以玉米的叶斑，灰色叶斑和图像为研究对象，利用计算机图像处理技术对颜色的有效分割和识别进行了研究。和形状特征。采用遗传算法对玉米病害图像的实时滤波选择进行优化。通过值平滑选择的图像的3 * 3模式噪声抑制;然后选择疾病的颜色特征提取中的HSV分量;类差异（OTSU）疾病形状字符分割和识别之间的最大值。结果表明，基于遗传算法的基于HSV的图像优化和Otsu方法可以更准确地对疾病的颜色和形状特征进行分割和识别，并提高了玉米病害图像检测和实时性和准确性。认识并针对物联网条件下的玉米病虫害提供技术支持。

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