Design and Realization of the SMT Product Character Recognition System

被引：0
|
作者：
Zhao, Huihuang [1 ,2 ]
Zhou, Dejian [1 ]
Wu, Zhaohua [3 ]
机构：
[1] Guangxi Univ Technol, Liuzhou, Guangxi, Peoples R China
[2] Xidian Univ, Sch Mech Elect Engn, Xian, Peoples R China
[3] Guilin Univ Elect Technol, Sch Mech & Elect Engn, Guilin, Guangxi, Peoples R China
来源：
MANUFACTURING ENGINEERING AND AUTOMATION I, PTS 1-3 | 2011年 / 139-141卷
关键词：
Character Recognition; Pattern Recognition; Back Propagation Neural Network; Surface Mount Technology; Image Processing;
D O I：
10.4028/www.scientific.net/AMR.139-141.1736
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We present an approach to recognizing characters in surface mount technology (SMT) product. An improved SMT product character recognition method is proposed which can obtain a good recognition rate. Some appropriate image processing algorithms, such as Gray processing, Low-pass Filter, Median Filter, and so on, are used to eliminate the noise. Then, Character image is obtained after character segmentation and character normalization. Finally, a three-layer back propagation (BP) neural network module is constructed. In order to improve the convergence rate of the network and avoid oscillation and divergence, the BP algorithm with momentum item is used. As a result, the SMT product character recognition system is developed. Experimental results indicate that the proposed character recognition can obtain satisfactory character-recognition rate and the recognition rate reached over by 98.6% when the hidden layer of BP neural network module has 20 nodes.
引用
收藏
页码：1736 / +
页数：2
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