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基于BP神经网络的数显仪表数字字符识别系统
引用本文:唐轶峻,申小阳,朱雯兰,隋成华. 基于BP神经网络的数显仪表数字字符识别系统[J]. 电测与仪表, 2005, 42(9): 42-45
作者姓名:唐轶峻  申小阳  朱雯兰  隋成华
作者单位:浙江工业大学,光电子研究所,杭州,310032;浙江工业大学,光电子研究所,杭州,310032;浙江工业大学,光电子研究所,杭州,310032;浙江工业大学,光电子研究所,杭州,310032
基金项目:浙江省教育厅资助项目;浙江省科技厅资助项目
摘    要:在化工、冶金等行业以及较为恶劣的环境场合下进行仪表数据的自动化采集,需要对仪表显示的动态数据进行自动识别,以判断是否满足控制条件。本文根据数字仪表图像的特点,运用区域生长算法定位仪表图像中的数据区域,采用投影法对字符串进行分割,最后应用BP神经网络法进行分类识别数字字符。实验结果表明,字符正确识别率达到96%。

关 键 词:图像预处理  区域生长  投影法  BP神经网络
文章编号:1001-1390(2005)09-0042-04
收稿时间:2005-05-07
修稿时间:2005-05-07

Recognition System for Character of Numeral Instrument Dynamic Displayed Based on BP Neural Network
TANG Yi-jun,SHEN Xiao-yang,ZHU Wen-lan,SUI Cheng-hua. Recognition System for Character of Numeral Instrument Dynamic Displayed Based on BP Neural Network[J]. Electrical Measurement & Instrumentation, 2005, 42(9): 42-45
Authors:TANG Yi-jun  SHEN Xiao-yang  ZHU Wen-lan  SUI Cheng-hua
Abstract:Data displayed by instrument need be usually automatically collected in chemical industry, metallurgy fields and some other dangerous condition, so it is important for the data to be recognized, thus the control system can judge whether they satisfied the control condition. According to the feature of numeral instrument image, region growing method is used to locate the data region which has reached ideal effect, projecting method is applied to segment the string, and the BP Neural Network to classify recognition numeral characters. The correct rate has reached 96 percent in experimentation
Keywords:image preprocessing   region growing   projecting method   BP neural network
本文献已被 CNKI 维普 万方数据 等数据库收录!
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