JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 4    Issue : 8    Date : August 2009

Vehicle License Plate Detection Method Based on Sliding Concentric Windows and Histogram
Kaushik Deb, Hyun-Uk Chae, and Kang-Hyun Jo
Page(s): 771-777
Full Text:
PDF (1,096 KB)


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, decomposing 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