柱面压印字符识别算法研究和实现  

Research and Implementation of Pressed Character Recognition Algorithm on Cylindrical Surface

作　　者：张传果 刘建群[1,2] ZHANG Chuanguo;LIU Jianqun(School of Electmmechanical Engineering,Guangdong University of Technology,Guangzhou Guangdong 510006,China;Guangdong Provincial Key Laboratory of Miero-Nano Manufacturing Technology and Equipment,Guangzhou Guangdong 510006,China)

机构地区：[1]广东工业大学机电工程学院,广东广州510006 [2]广东省微纳加工技术与装备重点实验室,广东广州510006

出　　处：《机床与液压》2018年第13期37-41,共5页Machine Tool & Hydraulics

基　　金：广东省科技计划项目(2015B010102012;2015B010101013;2016B090911001)

摘　　要：针对柱面压印字符与背景区域同色、且字符位于曲面上、成像质量差的情况,采用一种局部灰度区间最大化的缩放变换方法来凸显字符区域。提出一种先筛选字符区域后进行形态学优化的字符分割方法,能达到优化字符轮廓的效果;并且克服了传统方法直接用形态学优化造成的干扰区域粘连字符的弊病。最后创建训练文件对BP神经网络进行训练,对识别结果进行显示。实验结果表明:柱面压印字符识别算法高效稳定,字符识别正确率高,能够满足工业实际需求。According to characteristics of the pressed character on cylindrical surface with the same color as the background,the curved surface and the poor image quality,a scaling transformation method for local grey interval maximization is adopted to highlight the character region. Meanwhile a character segmentation method selecting character region before morphological optimization was proposed to achieve the optimization of character outline,and overcome the shortage of character adhesion in interference region caused by the traditional method using morphological optimization directly. Finally,the training file was created to train the Back-propagation（ BP） neural network,and recognition results were displayed. The experimental results show that the recognition algorithm of the pressed character has a good ability of robustness and high accuracy,entirely meeting the industrial requirements.

关 键 词：压印字符识别 灰度缩放变换 字符分割 BP神经网络 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]