计算机工程与应用2012，Vol.48Issue(4)：219-221,3.DOI:10.3778/j.issn.1002-8331.2012.04.064
一种新的不变矩与神经网络玉米病害识别系统
New system about moment invariant and neural network used in maize disease recognition
付立思 1何荣卜 1刘朋维1
作者信息
- 1. 沈阳农业大学信息与电气工程学院,沈阳110866
- 折叠
摘要
Abstract
According to the invariant moment theory, the binary and normalized maize disease images are obtained. A new and better 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 characteristics, 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.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Key words
maize disease recognition/ Hu moment invariant/ Radial Basis Function-Back Propagation(RBF-BP) neural network分类
信息技术与安全科学引用本文复制引用
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):219-221,3.
