Title :
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
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;
Conference_Titel :
Information and Communication Technology Convergence (ICTC), 2014 International Conference on
Conference_Location :
Busan
DOI :
10.1109/ICTC.2014.6983089