An Improved Character Recognition Framework for Containers Based on DETR Algorithm

Zhao, Xiaofang; Zhou, Peng; Xu, Ke; Xiao, Liyun

doi:10.3390/s21134612

Open AccessCommunication

An Improved Character Recognition Framework for Containers Based on DETR Algorithm

¹

Institute of Cognitive Computing and Intelligent Information, University of Science and Technology Beijing, Beijing 100083, China

²

Research Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China

³

Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China

^*

Author to whom correspondence should be addressed.

Sensors 2021, 21(13), 4612; https://doi.org/10.3390/s21134612

Submission received: 30 May 2021 / Revised: 23 June 2021 / Accepted: 28 June 2021 / Published: 5 July 2021

(This article belongs to the Special Issue Deep Learning for Object Detection, Classification and Tracking in Industry Applications)

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Abstract

An improved DETR (detection with transformers) object detection framework is proposed to realize accurate detection and recognition of characters on shipping containers. ResneSt is used as a backbone network with split attention to extract features of different dimensions by multi-channel weight convolution operation, thus increasing the overall feature acquisition ability of the backbone. In addition, multi-scale location encoding is introduced on the basis of the original sinusoidal position encoding model, improving the sensitivity of input position information for the transformer structure. Compared with the original DETR framework, our model has higher confidence regarding accurate detection, with detection accuracy being improved by 2.6%. In a test of character detection and recognition with a self-built dataset, the overall accuracy can reach 98.6%, which meets the requirements of logistics information identification acquisition.

Keywords: character recognition; DETR (detection with transformers); split-attention; multi-scale location coding

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MDPI and ACS Style

Zhao, X.; Zhou, P.; Xu, K.; Xiao, L. An Improved Character Recognition Framework for Containers Based on DETR Algorithm. Sensors 2021, 21, 4612. https://doi.org/10.3390/s21134612

AMA Style

Zhao X, Zhou P, Xu K, Xiao L. An Improved Character Recognition Framework for Containers Based on DETR Algorithm. Sensors. 2021; 21(13):4612. https://doi.org/10.3390/s21134612

Chicago/Turabian Style

Zhao, Xiaofang, Peng Zhou, Ke Xu, and Liyun Xiao. 2021. "An Improved Character Recognition Framework for Containers Based on DETR Algorithm" Sensors 21, no. 13: 4612. https://doi.org/10.3390/s21134612

APA Style

Zhao, X., Zhou, P., Xu, K., & Xiao, L. (2021). An Improved Character Recognition Framework for Containers Based on DETR Algorithm. Sensors, 21(13), 4612. https://doi.org/10.3390/s21134612

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An Improved Character Recognition Framework for Containers Based on DETR Algorithm

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