License Plate Recognition algorithm based on derived kernel

Author

Zhang, Zhen Chao ; Tang, Yuan Yan

Author_Institution

Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China

fYear

2012

fDate

15-17 July 2012

Firstpage

238

Lastpage

243

Abstract

License Plate Recognition (LPR) plays an important role on the traffic monitoring and parking management. In this paper, an updated algorithm is applied into the vehicle license plate identification, which is mainly based on derived kernel through visual cortex. With the two-layer derived kernel on neural response and first nearest classification method applied to character and numeral recognition, the errors caused by blur and noise can be reduced, so that the recognition accuracy can be improved on a certain of complex and unclear circumstance.

Keywords

character recognition; image classification; object recognition; traffic engineering computing; LPR; blur; character recognition; license plate recognition algorithm; nearest classification method; neural response; noise; numeral recognition; parking management; traffic monitoring; two-layer derived kernel; vehicle license plate identification; visual cortex; Accuracy; Algorithm design and analysis; Character recognition; Kernel; Licenses; Vehicles; Classification; Derived Kernel; License Plate Processing; License Plate Recognition; Neural Response;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on

Conference_Location

Xian

ISSN

2158-5695

Print_ISBN

978-1-4673-1534-0

Type

conf

DOI

10.1109/ICWAPR.2012.6294785

Filename

6294785