哈尔滨工程大学学报2024，Vol.45Issue(6)：1162-1169,8.DOI:10.11990/jheu.202208052
面向多复杂场景环境的敞车车号辨识研究
Research on coding identification of a convertible car in a complex environment
摘要
Abstract
Existing methods for locating and recognizing the number of convertible cars have problems with poor en-vironmental adaptability and low accuracy of location and recognition.In this study,a method for the accurate posi-tioning and recognition of a convertible car number in complex environments was presented.A framework of the model for the location of the convertible car number fused with multiscale feature information was built.On this ba-sis,the features of the multiscale pyramid were fused to design the car-number feature extraction network of a con-vertible car with a deep separable convolution.In addition,a vehicle number location recognition model based on the improved convolutional recurrent neural network(CRNN)was proposed,which was mainly designed for the structure of the recognition network model.The proposed method was verified using images of the convertible car compartment collected in different environments.The results reveal that the accuracy of the proposed vehicle num-ber location method is 0.94,and that of vehicle number recognition is 0.97.关键词
车号定位/深度可分离卷积/特征提取/改进卷积循环神经网络/特征金字塔/字符识别/铁路货运/深度学习Key words
vehicle number positioning/depthwise separable convolution/feature extraction/improved convolution-al recurrent neural network(CRNN):characteristic pyramid/character recognition/railway freight/deep learning分类
信息技术与安全科学引用本文复制引用
薛峰,于国丞,李世杰,凌烈鹏,张峰峰,陈峰炜..面向多复杂场景环境的敞车车号辨识研究[J].哈尔滨工程大学学报,2024,45(6):1162-1169,8.基金项目
中国铁道科学研究院集团有限公司科研开发基金项目(2022YJ099) （2022YJ099）
中铁科学技术开发有限公司基金项目(2022ZT05). （2022ZT05）
