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一种新的不变矩与神经网络玉米病害识别系统
引用本文:付立思,何荣卜,刘朋维. 一种新的不变矩与神经网络玉米病害识别系统[J]. 计算机工程与应用, 2012, 48(4): 219-221
作者姓名:付立思  何荣卜  刘朋维
作者单位:沈阳农业大学 信息与电气工程学院,沈阳 110866
摘    要:基于不变矩理论,对玉米病害图像进行二值化、图像归一化处理,提出一种新的、具有较好逼近能力和较强容错能力的RBF-BP神经网络识别系统。利用Hu不变矩特征的平移不变性、比例不变性、旋转不变性和对目标良好的抗干扰性等特性,处理复杂、多变的玉米病害图像,形成不变矩特征矢量样本库。根据Hu不变矩在提取图像特征过程中的可靠性、独立性及数目小的特点和RBF-BP神经网络在识别过程中较好收敛性特点,对玉米病害图像进行特征提取、网络训练和病害特征的识别。仿真实验结果表明RBF-BP神经网络系统的有效性。

关 键 词:玉米病害识别  Hu不变矩  径向基函数-反向传播(RBF-BP)神经网络  
修稿时间: 

New system about moment invariant and neural network used in maize disease recognition
FU Lisi , HE Rongbu , LIU Pengwei. New system about moment invariant and neural network used in maize disease recognition[J]. Computer Engineering and Applications, 2012, 48(4): 219-221
Authors:FU Lisi    HE Rongbu    LIU Pengwei
Affiliation:School of Information and Electronic Engineering, Shenyang Agriculture University, Shenyang 110866, China
Abstract:According to the invariant moment theory, the binary and normalized maize disease images are obtained. A new and bet- ter RBF-BP neural network recognition system with the approximation and the fault tolerance is proposed. The Hu invariant moment' s advantages that contain translation, proportion, rotation invariant and good anti-jamming are all used to deal with the complex and changeful maize disease images. According to the invariant moment' s reliability, independence, and little number of those characteris- tics, it can get a better convergence of recognition system to extract the maize image' s features and the training and recognition of RBF-BP neural network. The results of simulation show that the maize disease recognition of RBF-BP neural network has high accuracy and efficiency.
Keywords:maize disease recognition  Hu moment invariant  Radial Basis Function-Back Propagation(RBF-BP) neural network
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