An Algorithm Based on Text Position Correction and Encoder-Decoder Network for Text Recognition in the Scene Image of Visual Sensors

Zhiwei Huang; Jinzhao Lin; Hongzhi Yang; Huiqian Wang; Tong Bai; Qinghui Liu; Yu Pang

doi:10.3390/s20102942

An Algorithm Based on Text Position Correction and Encoder-Decoder Network for Text Recognition in the Scene Image of Visual Sensors

Sensors (Basel). 2020 May 22;20(10):2942. doi: 10.3390/s20102942.

Authors

Zhiwei Huang^{1

2}, Jinzhao Lin³, Hongzhi Yang³, Huiqian Wang³, Tong Bai³, Qinghui Liu³, Yu Pang³

Affiliations

¹ School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
² School of Medical Information and Engineering, Southwest Medical University, Luzhou, 646000, China.
³ Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

Abstract

Text recognition in natural scene images has always been a hot topic in the field of document-image related visual sensors. The previous literature mostly solved the problem of horizontal text recognition, but the text in the natural scene is usually inclined and irregular, and there are many unsolved problems. For this reason, we propose a scene text recognition algorithm based on a text position correction (TPC) module and an encoder-decoder network (EDN) module. Firstly, the slanted text is modified into horizontal text through the TPC module, and then the content of horizontal text is accurately identified through the EDN module. Experiments on the standard data set show that the algorithm can recognize many kinds of irregular text and get better results. Ablation studies show that the proposed two network modules can enhance the accuracy of irregular scene text recognition.

Keywords: encoder-decoder network; scene text recognition; text position correction; visual sensor.