Optical recognition of vehicle license plates

Abstract

This paper describes a new approach to analyze road images which often contain vehicles and extract license plate (LP) from natural properties by finding vertical and horizontal edges. In this paper, initially, segmentation technique named as sliding concentric windows (SCW) on the basis of a novel adaptive image segmentation technique for detecting candidate region. 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. Tilt correction in horizontal direction by the least square fitting with perpendicular offsets (LSFPO) is proposed and implemented for estimating rotation angle of the LP region. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by reorientation of the titled LP candidate through inverse affine transformation is proposed and implemented for removing shear from the LP candidates. Finally, statistical based template matching technique is used for recognition of Korean plate characters. Various LP images are used with a variety of conditions to test the proposed method and results are presented to prove its effectiveness.