Research on stamped character detection system based on TextBoxes

Hao Wei; Limin Cai; Dong Chen; Peizhi Zhao; Zhongyuan Lai

doi:10.1117/12.2690026

10 August 2023 Research on stamped character detection system based on TextBoxes

Hao Wei, Limin Cai, Dong Chen, Peizhi Zhao, Zhongyuan Lai

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 1274849 (2023) https://doi.org/10.1117/12.2690026
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

In order to realize the rapid detection of stenciled characters on castings in the industrial site, and to better classify and manage the castings, under the influence of complex environmental factors on the industrial site, the stenciled characters of castings have the characteristics of low contrast and inconspicuous edge features, etc., using deep learning. Methods An end-to-end OCR (Optical Character Recognition) casting steel stamp character recognition system was designed. By using the improved TextBoxes detection method on the input image to locate the target character area, combined with the CRNN (Convolutional Recurrent Neural Network) character recognition method to recognize and output the detected stamped characters, and at the same time augment the image data to improve the recognition accuracy. The results show that the model can reach 98.9% in recognition accuracy, and the average inspection time is 0.27S. It is superior to traditional template matching methods and other current mainstream deep learning target detection algorithms in recognition accuracy and speed. In terms of processing natural language information. It provides convenience and provides an effective means of human-computer interaction.

Citation Download Citation

Hao Wei, Limin Cai, Dong Chen, Peizhi Zhao, and Zhongyuan Lai "Research on stamped character detection system based on TextBoxes", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 1274849 (10 August 2023); https://doi.org/10.1117/12.2690026

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KEYWORDS

Optical character recognition

Object detection

Convolution

Tunable filters

Deep learning

Statistical modeling

Signal to noise ratio

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