光电工程, 2014, 41 (7): 37, 网络出版: 2014-08-18  

适应光照突变的工件字符识别系统

Workpiece Characters Recognizing System Adaptive to Illumination Mutations
作者单位
1 中国科学院光电技术研究所,成都 610209
2 电子科技大学 光电信息学院,成都 610054
3 中国科学院大学,北京 100049
摘要
为了实现机械工件上刻写字符的自动检测、识别与显示,本文设计并完成工件字符自动识别系统。重点针对光照变化时工件字符难以识别的问题,研究不同光源组合方式对系统识别性能的影响,提出了一种能更好适应光照突变的特征提取算法。首先,对输入图像利用优化的同态滤波算法增加字符的细节信息,减低光源照度的影响。然后,分别采用基于LOG 算子的自适应阈值法获取图像的整体轮廓和全局特征,采用局部二值模式(LBP)算法获得对光照突变不敏感的LBP 纹理特征。最后,联合目标全局特征和LBP 局部纹理特征对应像素做相关运算,获得对光照不敏感的融合特征向量。在工业现场进行实测,测试结果表明:识别率平均达到94.72%,对工件平均检测时间230 ms,满足实时性要求。与SIFT 算法和Bayesian 算法相比,在光照突变情况下本系统的识别精度和稳定性更有优势,且满足工业应用上自动识别的要求,并已实际用于工业测量。
Abstract
In order to realize automatic detection, identification and display lettered characters on the workpiece,automatic recognition system of workpiece is designed and achieved. The designed system can solve the problem that workpiece characters are difficultly recognized in the situation of the light abrupt changing. According to effects of different light sources combinations for character recognition performance, a novel algorithm of feature extraction is proposed to adapt light mutations. Firstly, the character details are enhanced by using homomorphic filtering operator.Then, contour and global features are respectively gained by utilizing adaptive threshold algorithm based on LOG while texture feature map is obtained by using local binary pattern (LBP). Finally, two feature in the same image position are combined by “OR” operator to gain light insensitive fusion feature. In the industrial circumstance, the extensive measurement results demonstrate that the recognition accuracy of detecting system reaches 94.72% and the average execution time is 230 ms. Compared to the SIFT and Bayesian algorithms, our system’s accuracy better satisfied the requirements of automatic recognition in industrial applications and the method has been used for industrial measurement.

常永鑫, 余化鹏, 徐智勇, 张静, 高椿明. 适应光照突变的工件字符识别系统[J]. 光电工程, 2014, 41(7): 37. CHANG Yongxin, YU Huapeng, XU Zhiyong, ZHANG Jing, GAO Chunming. Workpiece Characters Recognizing System Adaptive to Illumination Mutations[J]. Opto-Electronic Engineering, 2014, 41(7): 37.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!