A novel license plate character segmentation method for different types of vehicle license plates

Author

Sarker, Md Mostafa Kamal ; Moon Kyou Song

Author_Institution

Dept. of Electron. Convergence Eng., Wonkwang Univ., Iksan, South Korea

fYear

2014

fDate

22-24 Oct. 2014

Firstpage

84

Lastpage

88

Abstract

License plate character segmentation (LPCS) is a very important part of vehicle license plate recognition (LPR) system. The accuracy of LPR system widely depends on two parts; namely license plate detection (LPD) and LPCS. Different country has different types and shapes of LPs are available. Based on character position on LP, we can find two types of LPs over the world, single row (SR) and double rows (DR) LP. Most of the LPCS methods are generally used for SRLP. This paper proposed a novel LPCS method for SR and DR types of LPs. Experimental results shows the real-time effectiveness of our proposed method. The accuracy of our proposed LPCS method is 99.05% and the average computational time is 27ms which is higher than other existing methods.

Keywords

character recognition; image recognition; image segmentation; object detection; LPCS; LPD; LPR system; license plate character segmentation; license plate detection; vehicle license plate recognition; Accuracy; Histograms; Image color analysis; Image segmentation; Licenses; Object segmentation; Vehicles; Traffic surveillance; character segmentation; image processing; license plate verification; region of interest;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technology Convergence (ICTC), 2014 International Conference on

Conference_Location

Busan

Type

conf

DOI

10.1109/ICTC.2014.6983089

Filename

6983089