Open AccessLicense Plate Character Segmentation Algorithm Based on Improved Regression Model
Author(s) -
Yongyi Yang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1453/1/012030
Subject(s) - segmentation , license , character (mathematics) , artificial intelligence , pattern recognition (psychology) , computer science , regression , regression analysis , character recognition , image segmentation , algorithm , computer vision , mathematics , image (mathematics) , machine learning , statistics , geometry , operating system
Many character segmentation algorithms in license plate recognition system are not very good for segmentation of complex characters, and there is a phenomenon of character sticking, which results in slow recognition speed and not very good recognition effect of the license plate with complex characters. For such problems, a segmentation algorithm based on the improved regression model on statistical characteristics is presented. Compared with other algorithms, experimental results show that less time is consumed and segmentation effect is better. The recognition rate of license plate can be improved effectively.