Title: Automatic number plate recognition system by character position method
Authors: Birmohan Singh; Manpreet Kaur; Dalwinder Singh; Gurwinder Singh
Addresses: Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal (PB), 148106, India ' Department of Electrical and Instrumentation Engineering, Sant Longowal Institute of Engineering and Technology, Longowal (PB), 148106, India ' Department of Computer Science, Punjabi University, Patiala (PB), 147002, India ' Department of Computer Science, Punjabi University, Patiala (PB), 147002, India
Abstract: Automatic number plate recognition (ANPR) is an important image processing technology used to recognise number plates of vehicles. Plate localisation and character recognition are two stages of ANPR. In this paper, a methodology has been proposed to develop robust ANPR system. A new algorithm has been proposed for number plate localisation which is based on character positioning method. Character recognition is done with support vector machine in which feature vector is calculated by recursive sub-divisions of character image. The problem of similar shape characters has been solved by syntactic analysis of number plate format for a particular geographical region. The system has been tested on 419 sample images from various countries with various variations in viewing angles, illuminations and distances. Experimental results show that the proposed system detects number plates and recognise characters successfully. The overall success rate of plate localisation is 97.21% and recognition of number is 95.06%.
Keywords: image segmentation; automatic number plate recognition; ANPR; number plate localisation; NPL; mathematical morphology; support vector machines; SVM; image processing; vehicle number plates; character recognition; character position.
DOI: 10.1504/IJCVR.2016.073761
International Journal of Computational Vision and Robotics, 2016 Vol.6 No.1/2, pp.94 - 112
Received: 03 Jan 2014
Accepted: 02 Nov 2014
Published online: 18 Dec 2015 *