A comparison study on motorcycle license plate detection

Abstract

License plate detection and recognition are mostly studied on automobiles but only few on motorcycles. As motorcycles are becoming popular for local transportation and environmental friendliness, the demands for license plate recognition have been increasing in recent years. The primary difference between the license plate recognition in automobiles and motorcycles is on the detection of license plates, which is the topic of this study. For automobiles, the license plates are mostly installed on the front or on the back of the vehicle with relatively less complicated backgrounds; however, for motorcycles, the backgrounds can be far more complicated. To better handle complicated backgrounds, we study the case with motorcycle detection as preprocessing so that the search area for the license plate can be better constrained, and compare its performance with the case without the preprocessing. A few detection methods are configured and studied for both the motorcycle detection and license plate detection, including the state-of-the-art part-based model. Considering processing speed and accuracy, the histogram of oriented gradients (HOG) with support vector machines (SVMs) is found to be the best detector for motorcycle license plates.