Recognition method of container number in complex scene based on improved EAST network

YeCheng Peng; Chen Dong; ShuWei Zhang

doi:10.1117/12.2639519

19 May 2022 Recognition method of container number in complex scene based on improved EAST network

YeCheng Peng, Chen Dong, ShuWei Zhang

Proceedings Volume 12250, International Symposium on Computer Applications and Information Systems (ISCAIS 2022); 1225013 (2022) https://doi.org/10.1117/12.2639519
Event: International Symposium on Computer Applications and Information Systems (ISCAIS2022), 2022, Shenzhen, China

Abstract

With the rapid development of global shipping industry, intelligent recognition of container number has become a hot spot of application. However, the containers are usually outdoors, which often can't reach the normal recognition environment of characters. For complex scenes such as corrosion, tilt, blur and uneven characters, the traditional text recognition methods are not ideal due to high time-consuming and multi-stage reasons. In this paper, a new method for recognition of container number of port is proposed. Based on the deep learning algorithm, the multi-layer neural network is used to identify features of multiple dimensions, enhancing the algorithm's ability to identify container number in complex scene. The method consists of four parts, the original container image is processed by the improved EAST network, AddMargin, CRNN network and calculation operation of check digit, the accurate container number can be obtained as the result. Through experiments, 3961 samples of container images were tested, and the accurate rate of recognition of container number could reach 94.14% (3729/3961), and the detection speed was 1.20 seconds per image.

Citation Download Citation

YeCheng Peng, Chen Dong, and ShuWei Zhang "Recognition method of container number in complex scene based on improved EAST network", Proc. SPIE 12250, International Symposium on Computer Applications and Information Systems (ISCAIS 2022), 1225013 (19 May 2022); https://doi.org/10.1117/12.2639519

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