A new car logo extraction method based on license plate detection

Abstract

Abstract Nowadays, intelligent transportation system is becoming the new trend because of the development of modern traffic, which serves to help gather traffic data, control traffic and improve road safety. One big challenge within intelligent transportation system is car model detection, which provides important information for traffic monitoring and planning. Currently, most car model extraction focus more on one-pass solution, which directly finds out the car logo region. In this paper, a new hybrid car logo extraction method based on license plate detection is proposed. First, a text detection is applied on car images to locate the license plate. Then, within a region of interest above license plate, a sub region is extracted to locate the car logo based on edge information. The fundamental concept is that using the relative location information between the license plate and car logo can take the most advantage of existing state-of-the-art license plates detection methods which is practically accurate, robust and efficient. Experimental results on OpenALPR dataset demonstrate its good performance in extracting car logos.