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http://dx.doi.org/10.9717/kmms.2022.25.4.568

A Study on the License Plate Recognition Based on Direction Normalization and CNN Deep Learning  

Ki, Jaewon (Dept. of Electronic & Electrical Eng., Graduate School, Hongik University)
Cho, Seongwon (Dept. of Electronic & Electrical Eng., Graduate School, Hongik University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.4, 2022 , pp. 568-574 More about this Journal
Abstract
In this paper, direction normalization and CNN deep learning are used to develop a more reliable license plate recognition system. The existing license plate recognition system consists of three main modules: license plate detection module, character segmentation module, and character recognition module. The proposed system minimizes recognition error by adding a direction normalization module when a detected license plate is inclined. Experimental results show the superiority of the proposed method in comparison to the previous system.
Keywords
Licence plate recognition; Character segmentation; Character recognition; Direction normalization; Mask R-CNN;
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Times Cited By KSCI : 1  (Citation Analysis)
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