An Efficient Methodology for License Plate Localization and Recognition with Low Quality Images

Abstract

It is challenging to find an effective license plate detection and recognition method due to the different conditions during the image acquisition phase. This paper aims to develop a new accurate and efficient method based on color difference and SVM recognition model that yields better performance for vehicle images under low quality. The proposed method is tested with 200 images which involve many difficult conditions, such as low resolution, night-lighting, dirt, complicated background, and distortion problems. The experimental results demonstrate very satisfactory performance for license plate detection in terms of speed and accuracy and are better than the existing methods like edge detection or HSV color conversion method. The overall probability of localization is close to 100%, with a false recognition rate of 2%.