激光与光电子学进展, 2019, 56 (19): 191506, 网络出版: 2019-10-12   

智能车道路场景数字字符识别技术 下载: 825次

Digital Character Recognition Technique for Intelligent Vehicles in Road Scenes
作者单位
陆军军事交通学院, 天津 300161
摘要
针对道路场景中数字字符高噪声、多视角和难以定位识别的问题,提出了一种稳健的道路场景数字字符定位识别算法。采用基于色彩空间和边缘增强的最大稳定极值区域(MSER)算法来提取候选区域,设计了几何约束滤波器,并与笔画宽度变换(SWT)联合滤除非字符区域,得到字符定位结果。对Lenet-5中的收敛函数和池化窗进行改进,将定位后的字符区域归一化输入网络中,得到最终的字符识别结果。实验结果表明,本文算法的字符召回率达到90.0%,综合性能值达到0.89,字符识别率达到88.6%,优于同类算法性能。
Abstract
To address the problems of large noise, multi-view, and difficult to locate and identify digital characters in road scenes, a robust method for recognizing digital characters in road scenes is proposed. According to this method, the maximally stable extremum region algorithm based on the color space and enhanced edge is used first to obtain candidate regions. Then, a geometrically constrained filter is designed and combined with the stroke width transform to filter non-character regions. The convergence function and pooling window of Lenet-5 are improved, and the localized character regions are normalized and input into the network to obtain the final recognition results. According to the experimental results, the recall rate of the proposed method is 90.0%, the comprehensive performance value is 0.89, and the character recognition rate is 88.6%. These results are higher than those of the existing algorithms.

白睿, 徐友春, 李永乐, 李炯, 谢枫. 智能车道路场景数字字符识别技术[J]. 激光与光电子学进展, 2019, 56(19): 191506. Rui Bai, Youchun Xu, Yongle Li, Jiong Li, Feng Xie. Digital Character Recognition Technique for Intelligent Vehicles in Road Scenes[J]. Laser & Optoelectronics Progress, 2019, 56(19): 191506.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

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!