Size-self-adaptive recognition method of vehicle manufacturer logos based on feature extraction and SVM classifier

Abstract

Besides their decorative purposes, vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information retrieval. However, unlike the license plate, which is designed for identification purposes, vehicle manufacturer logos are mainly designed for decorative purposes such that they might lack discriminative features themselves. Moreover, in practical applications, the vehicle manufacturer logos captured by a fixed camera vary in size. For these reasons, detection and recognition of vehicle manufacturer logos are very challenging but crucial problems to tackle. In this paper, based on preparatory works on logo localization and image segmentation, we propose a size-self-adaptive method to recognize vehicle manufacturer logos based on feature extraction and support vector machine (SVM) classifier. The experimental results demonstrate that the proposed method is more effective and robust in dealing with the recognition problem of vehicle logos in different sizes. Moreover, it has a good performance both in preciseness and speed.