摘要
针对轴承上字符的特点,提出了一种基于机器视觉的轴承字符自动识别方法,并利用C++和OpenCV计算机视觉库开发了识别软件。对轴承字符图像进行阈值分割,使用Sobel算子提取边缘轮廓,然后使用改进的圆检测算法定位环形字符区域,在经过极坐标变换后进行字符分割。最后提取改进的字符特征,使用支持向量机分类器进行字符识别。试验结果表明:该方法能有效识别轴承字符,而且识别率达到了95%以上,具有广阔的应用前景。
According to the characteristics of bearing characters,an automatic identification method based on machine vision is proposed.The detection software was developed on C++and OpenCV computer vision library.Firstly,the bearing character image was segmented by threshold,then the edge contour was extracted by Sobel operator,then the circular character region was located by using the improved circle detection algorithm,and character segmentation was performed after the polar coordinate transformation.Finally,the improved character features were extracted,and the support vector machine(SVM)classifier was used for character recognition.Experimental results show that the method can effectively identify bearing characters,and the recognition rate reaches over 95%,which has broad application prospects.
作者
任永强
潘浩
李广涛
REN Yongqiang;PAN Hao;LI Guangtao(School of Mechanical and Engineering,Hefei University of Technology,Hefei Anhui 230009,China)
出处
《机床与液压》
北大核心
2020年第5期11-14,共4页
Machine Tool & Hydraulics
基金
国家重点研发项目(2018YFB0104600)
安徽省科技重大专项(17030901062)。
关键词
机器视觉
圆检测
字符识别
支持向量机
Machine vision
Circle detection
Character recognition
Support vector machine
作者简介
任永强(1968-),男,博士,副教授,研究方向为精密测量、汽车成套自动化装备及测控研究。E-mail:342474609@qq.com。
