Abstract
This paper presents algorithms for vision-based classification of vehicles based on vehicle logo in monocular image of traffic scenes recorded by a stationary camera. The intended application is automatic recognition of vehicle type for secure access and traffic monitoring applications, a problem not hitherto considered at such a level of accuracy. In recognition of vehicle type, differing with other researchers who attend to the recognition of shape, size of vehicle, we pay attention to the location and recognition of vehicle logo. The vehicle logo is unique mark of vehicle type (both make and model). We demonstrate that a relatively simple vehicle logo recognition method from front images can be used to obtain high performance verification and recognition of vehicle type. Firstly, the vehicle logo can be rough detected by prior knowledge, such as license, and then logo can be exactly detected by edge feature. Finally, the logo can be recognized using template matching and edge orientation histograms. Experimental results show the effectiveness of the proposed method.
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