文献类型：期刊文献

英文题名：Automatic container code localization and recognition via an efficient code detector and sequence recognition

作者：Li, Chenghao[1]; Liu, Shuang[1]; Xia, Qiaoyang[1]; Wang, Hui[1]; Chen, Haoyao[2]

机构：[1] School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] State Key Laboratory of Robotics and System, School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, China

年份：2019

卷号：2019-July

起止页码：532

外文期刊名：IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

收录：EI(收录号：20194507620118)

语种：英文

外文关键词：Statistical tests

摘要：The challenge of container code localization and recognition is that the code varies in size, position, and arrangements according to the container style and environmental changes. This paper proposes an automatic container code localization and recognition system via an efficient code detector and a sequence recognizer. The code detector locates text features on the backend of the container and extracts the code through segmentation, which increases the stability of code localization. The proposed recognition algorithm regards the code as three separate sequences and recognizes them through a recurrentconvolutional neural network to improve efficiency and accuracy. To verify the validity, a test dataset is established containing about 700 high-resolution images and over 2000 gray-scale code patches. The proposed code localization and recognition algorithm is verified on the dataset in experiments and achieves overall accuracy of 93.98% at about 0.1s per-frame. ? 2019 IEEE.