Title :
An Efficient Method for Correcting Vehicle License Plate Tilt
Author :
Deb, Kaushik ; Vavilin, Andrey ; Jo, Kang-Hyun
Author_Institution :
Dept. of Electr. Eng. & Inf. Syst., Univ. of Ulsan, Ulsan, South Korea
Abstract :
Tilt correction is a very crucial and inevitable task in the automatic recognition of the vehicle license plate (VLP). In this paper, according to the least square fitting with perpendicular offsets (LSFPO) the VLP region is fitted to a straight line. After the line slope is obtained, rotation angle of the VLP is estimated. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by inverse affine transformation is proposed for removing shear from the LP candidates. Despite the success of VLP detection approaches in the past decades, a few of them can effectively locate license plate (LP), even when vehicle bodies and LPs have similar color. A common drawback of color-based VLP detection is the failure to detect the boundaries or border of LPs. In this paper, we propose a modified recursive labeling algorithm for solving this problem and detecting candidate regions. According to different colored LP, these candidate regions may include LP regions. Geometrical properties of the LP such as area, bounding box and aspect ratio are then used for classification. Various LP images were used with a variety of conditions to test the proposed method and results are presented to prove its effectiveness.
Keywords :
affine transforms; computational geometry; curve fitting; image colour analysis; image recognition; least squares approximations; traffic engineering computing; automatic vehicle license plate recognition; inverse affine transformation; least square fitting; line slope estimation; recursive labeling algorithm; rotation angle estimation; vehicle license plate tilt correction method; Histograms; Image color analysis; Image segmentation; Labeling; Licenses; Object segmentation; Vehicles; affine transformation; and recursive labeling algorithm; least square fitting with perpendicular offsets (LSFPO); tilt correction;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.135