Abstract
With the increasing number of cameras available in the cities, there is an increasing interest in recognizing license plate of two wheelers riders who do not wear helmet. This can be performed in four stages, background modeling, vehicle detection, helmet detection and automatic license plate recognition. This work is focused on the background modeling to extract foreground objects from its background. In this work, a 2-step method is proposed. The first step proposes and uses a key frame identification algorithm to extract a set of optimal frames. The background subtraction is then performed on these frames in the second step. A discrete wavelet packet transformation based method is used to separate background and foreground objects. Experimental results prove that the proposed algorithm is more effective when compared with the existing approaches.
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