A new method for general work piece recognition based on Neural Network

被引:0
|
作者
He, Zeqiang [1 ]
Ma, Jiachen [1 ]
Li, Zonglin [1 ]
机构
[1] Harbin Inst Technol, Harbin 150001, Peoples R China
关键词
Invariant moments; BP neural network; Wavelet neural network; Ada-boost; image recognition; FEATURE-EXTRACTION; CLASSIFIER;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a new method for general work piece recognition based on Wavelet Neural Network is proposed. The composition of the experimental system is introduced and the operating principle is analyzed. The invariant moment is a highly concentrated image feature, which have the characteristics of invariant to translation and rotation. In the selection of the classifier, the Wavelet Neural Network is adopted in that this method has the great advantage of fast training speed and high recognition rate relative to BP Neural Network. Ada-boost is employed because no matter which kind of neural network is used, we can use it to improve the recognition accuracy of the neural network. This is a very wide range of network performance improvement method. The experimental results illustrate that the image recognition method based on "wavelet neural network + ada-boost" has better ability of classification.
引用
收藏
页码:3428 / 3433
页数:6
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