Vehicle logo recognition based on the hybrid feature of Zernike moments and HOG gradient histogram

• 1、School of Electronics and Information Engineering,Tongji University,Shanghai,201804

Abstract：Vehicle logo recognition technology is an important area of the intelligent transportation system. When license plate is defaced or veiled artificially in traffic surveillance video, it's hard to confirm the information of the car, this is an important problem in the intelligent transportation system. The vehicle logo, as a key feature of a car, can play a better role in the secondary discrimination.Vehicle logo recognition aims to recognize the logo information of the vehicle by coupling the methods of computer vision, image processing and pattern recognition. Vehicle logo recognition system consists of two key components: vehicle logo detection and vehicle logo recognition .This paper presents a method that can effectively identify the vehicle logo which has been located. In this paper, a new vehicle identification feature is proposed by combining Zernike moments and HOG gradient histogram, which can used as the input of SVM classifier to classify vehicle logo. Experimental results show that the hybrid feature has stronger adaptability and robustness than Zernike moments or HOG parallel gradient histogram features in terms of resisting interference such as resisting rotation, light, noise which can effectively reduce false detection rate of vehicle logo recognition.

Keywords： Vehicle Logo Recognition； Zernike Moments；HOG Gradient Histogram Features；SVM