基于多层卷积滤波与HSV颜色提取的茶轮斑病识别研究

摘要

利用卷积滤波对原始图像进行显示轮廓以及锐化处理,引入了HSV模型进行颜色提取,通过二值化再次滤波完成了茶轮斑病斑区的提取,实现茶叶的茶轮斑病的快速诊断.结果表明,采用卷积滤波与HSV模型等图像处理技术能够较好地识别茶轮斑病的病斑区,对于图像清晰、面积大的病斑区识别比较精确.利用Python语言的嵌入性,为进一步实现茶叶茶轮斑病的精准喷雾系统打下了基础.%The original image is depicted and sharpen by convolution filtering, and then put it in HSV model to obtain the image color extraction. In order to get the target area of the tea wheel spot,it is also used the image binaryzation to complete the refiltering.Finally,that is a picture rapid diagnosis of tea leaf spot disease. The results showed that the image recognition of tea leaf spot in leaves of tea leaves was finished. By using convolution filtering and HSV model image processing technolo-gy can be better identified the round spot of tea lesion area, especially the clear image,size of lesion area. Taking advantage of the embeddedness of Python language,it lays the foundation for the accurate spray system of tea tea wheel spot disease.