Vehicle License Plate Detection Method Based on Sliding Concentric Windows and Histogram Kaushik Deb, Hyun-Uk Chae and Kang-Hyun Jo Graduate School of Electrical Engineering and Information Systems, University of Ulsan, Ulsan, Korea Email: {debkaushik99, hwchae, jkh2008}@islab.ulsan.ac.kr Abstract— Detecting the region of a license plate is the key component of the vehicle license plate recognition (VLPR) system. A new method is adopted in this paper to analyze road images which often contain vehicles and extract LP from natural properties by finding vertical and horizontal edges from vehicle region. The proposed vehicle license plate detection (VLPD) method consists of three main stages: (1) a novel adaptive image segmentation technique named as sliding concentric windows (SCWs) used for detecting candidate region; (2) color verification for candidate region by using HSI color model on the basis of using hue and intensity in HSI color model verifying green and yellow LP and white LP, respectively; and (3) finally, decom- posing candidate region which contains predetermined LP alphanumeric character by using position histogram to verify and detect vehicle license plate (VLP) region. In the proposed method, input vehicle images are commuted into grey images. Then the candidate regions are found by sliding concentric windows. We detect VLP region which contains predetermined LP color by using HSI color model and LP alphanumeric character by using position histogram. Experimental results show that the proposed method is very effective in coping with different conditions such as poor illumination, varied distances from the vehicle and varied weather. Index Terms— Vehicle license plate detection (VLPD), HSI color model and histogram. I. I NTRODUCTION With the rapid development of highway and the wide use of vehicle, people start to pay more and more attention on the advanced, efficient and accurate intelligent trans- portation systems (ITSs). The task of recognizing specific object in an image is one of the most difficult topics in the field of computer vision or digital image processing. VLPD is also very interesting in finding license plate area from vehicle image. The vehicle license plate detection is widely used for detecting speeding cars, security control in restricted areas, unattended parking zone, traffic law enforcement and electronic toll collection. Last few years have seen a continued increase in the need for and use of VLPR. The license plate detection is an important research topic of VLPR system. Because of different conditions such as poor illumination and varied weather, it is important and interesting how to segment license plate fast and perfectly from road images which often contain vehicles. The focus of this paper is on the consolidation of a new image segmentation method implemented in a VLPD system. Specifically our contribution in image segmentation is unique as: Image segmentation method named as sliding concen- tric windows (SCW) used for analyzing road images which often contain vehicles and extract LP from natural properties by finding vertical and horizontal edges from vehicle region. Furthermore, color verification for candidate regions by using HSI color model on the basis of using hue and intensity in HSI color model is verified by green and yellow LP and white LP, respectively. Finally, decom- posing candidate region which contains predetermined LP alphanumeric character by using position in the histogram to verify and detect vehicle license plate region is per- formed. The rest of this paper is organized as follows. The next section composes a review of similar researches that have been implemented and tested for vehicle license plate detecting. In Section III, the specific features of Korean VLP to be considered are described. In Section IV, the proposed VLPD algorithm is described. The three primary stages of the proposed VLPD algorithm, i.e. detecting candidate regions, authenticating candidate region color and character extraction of LP region are discussed in details in Section V. In Section VI, experimental results are reported. Finally, some conclusions are given and future work is proposed in Section VII. II. REVIEW OF OTHER METHODS This section provides a descriptive summary of some methods that have been implemented and tested for VLPD. As far as detection of the plate region is con- cerned, researchers have found many methods of locating license plate. For example, a method based on image seg- mentation technique named as sliding windows (SW) was also proposed for detecting candidate region (LP region) [1], main thought of image segmentation technique in LP can be viewed as irregularities in the texture of the image and abrupt changes in the local characteristics of the image, manifesting probably the presence of a LP. A conventional statistical classifier based on the k nearest neighbours rule is used to classify every pixel of a test JOURNAL OF COMPUTERS, VOL. 4, NO. 8, AUGUST 2009 771 © 2009 ACADEMY PUBLISHER