基于粗糙集和BP神经网络的棉花病害识别OA北大核心CSCDCSTPCD
Cotton diseases identification based on rough sets and BP neural network
为了提高棉花病害的识别率,提出了一种在自然环境条件下基于粗糙集和BP神经网络的棉花病害识别方法.该方法以轮纹病、角斑病、褐斑病和盲椿象为研究对象,将病害棉花图像从RGB颜色空间转换到HSI和L*a*b*颜色空间,应用Otsu算法对H分量、a*分量和b*分量进行阈值分割,通过H+a*+b*分量与原始图像的交集提取棉花病斑区域,利用颜色矩和灰度共生矩阵分别提取病斑的颜色和纹理特征,并结合粗糙集理论和BP神经网络,实现特征向量的优选,和棉花病害的识别.…查看全部>>
In order to improve the recognition rate of cotton diseases, an identification method of cotton diseases based on rough sets and BP neural network under natural environmental conditions was presented. In this method, Otsu method was used to get the threshold of//, a and b* components from four cotton diseases colored images in the HIS and/,*aV color spaces, and diseased regions of cotton were extract by intersection with H+a +b component and original image. …查看全部>>
张建华;祁力钧;冀荣华;王虎;黄士凯;王沛
中国农业大学工学院,北京100083现代农业装备优化设计北京市重点实验室中国农业大学工学院,北京100083现代农业装备优化设计北京市重点实验室中国农业大学信息与电气工程学院,北京100083现代农业装备优化设计北京市重点实验室
信息技术与安全科学
棉花病害识别粗糙集BP神经网络
cottondiseasesidentificationrough setBP neural network
《农业工程学报》 2012 (7)
161-167,7
中央高校基本科研业务费专项资金资助(编号:KYCX2011072)
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