Abstract: For timely diagnose and prevent the rice diseases,computer technology and image processing technology were used for disesae diagnosis. Python crawler technology was used to compile image crawler programs based on rice disease keywords.The feature matching of Matlab image was used to filter the image set to improve the accuracy of image collection.The results showed that the extraction accuracy of rice disease images obtained only by Python crawler technology was higher than 50. 00%,except bipolaris oryzae.Among them,the extraction effect of gibberellic disease was the best,with an accuracy rate of 72.7%.The false detection rate of images after the feature matching screening was below 6.00%,which not only improved the accuracy of data collection,but also showed that rice diseases image acquisition through the intelligent method was feasible.

Key words: Rice disease, Python, Feature matching, Image processing, Agricultural information

摘要： 为及时诊断和防治水稻病害，通过计算机技术和图像处理技术进行病害诊断。利用Python爬虫技术编写基于水稻病害关键词的图像爬虫程序，在此基础上使用Matlab图像处理模块的特征匹配对图像集进行筛选，提高图像采集的准确度。结果表明，只利用Python爬虫技术获取的水稻病害图像，除胡麻叶斑病外，提取的准确率均高于50.00%，其中赤霉病提取效果最好，准确率达到72.7%。而通过特征匹配筛选后图像错检率在6.00%以下，不仅提高了数据采集的精度，也表明水稻病害图像智能采集方法可行。

关键词: 水稻病害, Python, 特征匹配, 图像处理, 农业信息