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In order to recognize multi-class vehicles, traditional methods are typically based on license plates and frontal images of vehicles. These methods rely heavily on specific datasets and thus are not applicable in real-world tasks. In this paper, we propose a novel method based on a hierarchical model, HMAX, which simulates visual architecture of primates for object recognition. It can extract features...
This paper presents a new method for the vehicle license plate and the frontal mask localization. The proposed license plate localization initializes candidate regions based on maximally stable extremal regions (MSERs). Then, the candidate regions are categorized into three classes of license plate character components, plate background components and the other components by using intensity, size,...
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