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文章摘要
基于改进Hough变换和BP网络的指针仪表识别
Pointer Instrument Recognition Based on BP Network and Improved Hough Transform
Received:September 25, 2014  Revised:September 25, 2014
DOI:
中文关键词: 指针仪表  字符识别  Hough变换  BP神经网络
英文关键词: Pointer instrument  Character recognition  Hough transform  BP neural network
基金项目:
Author NameAffiliationE-mail
Zhu Haixia* Daqing Oilfield Co Power Group,Daqing,Heilongjiang,163000 zhuhaixiaxueshu@163.com 
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中文摘要:
      指针仪表示数的视觉识别,对于提高电气、机械、汽车等工业领域的生产效率具有重要意义。采用Hough变换方法完成指针直线特征的识别,进而在表盘圆形特征的识别过程中对Hough变换方法进行了改进,通过减少累加像素数目结合灰度中心法来提高原性特征定位的效率和精度。在字符识别阶段,构建了一个三层次的BP神经网络。实验结果表明,本文方法对于Hough变换的改进措施达到了预期效果,BP神经网络也实现了字符特征的准确识别。
英文摘要:
      Visual identification of pointer instrument number has important significance to improve production efficiency of the electrical, mechanical, and automotive industry. In this paper, Hough transformation method was used in recognition of linear feature of pointer, and then dial circular feature was identified by an improved Hough transform. This work was completed by reducing the accumulated number of pixels and combining the gray center method. In the character recognition stage, BP neural network is built with a three level structure. Experimental results show that, this method achieves the expected effect for improving measures of Hough transform, and accurate recognition of characters can be obtained by using BP neural network.
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