Title :
License Plate Character Segmentation and Recognition Based on RBF Neural Network
Author_Institution :
Coll. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
Abstract :
Character segmentation and recognition is the research hotspot of vehicle license plate recognition technology. A new method is presented in this paper. Based on the vehicle license location, the segment method of vertical projection information with prior knowledge is used to slit characters, and extract the statistical features. Then the RBF neural network is used to recognize characters with the feature vector as input. The results show that this method can recognize characters precisely and improve the ability of license plate character recognition effectively.
Keywords :
character recognition; image recognition; image segmentation; radial basis function networks; RBF neural network; license plate character recognition; license plate character segmentation; prior knowledge; vehicle license location; vehicle license plate recognition; vertical projection information; Character recognition; Data mining; Educational technology; Feature extraction; Image recognition; Image segmentation; Intelligent transportation systems; Licenses; Neural networks; Vehicles; License plate character recognition; RBF neural network; feature extraction; vertical projection;
Conference_Titel :
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6388-6
Electronic_ISBN :
978-1-4244-6389-3
DOI :
10.1109/ETCS.2010.464