Visual Attention Saliency Model for License Plate Location

Abstract

In order to locate the license plate in noisy background or various illumination conditions, a license plate location model based on visual attention is proposed, which imitates the biological mechanism of human visual. Four major visual sensitive characteristics of Chinese license plate are applied. First, the features of intensity, color and texture are extracted and integrated to structure the saliency map; second, the obtaining the optimal threshold based on the shape feature for foreground segmentation; at last, support vector machine is applied to eliminate the false plates in the image. Experimental results show that the proposed model is adaptive to various illumination conditions, complicated background, and resistant to noise.