Computer School, China West Normal University, Nan Chong, Sichuan, 637009, P.R China

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Abstract—We propose a novel method for license plate detection in nighttime videos with complicated background scenes. The proposed method use multi-features-based combination way in the residual edge image. Our work firstly is color space conversion from RGB to La*b* color space and get enhancement L component of license plate image, then extract out multi-features of license plate, thirdly, multi-features combination method is used to get license plate detection, finally, search the license plate localization and segment the characters from the original nighttime environment images by using nonlinear vector quantization method. The experimental results show that the proposed method has more robust to interference characters and more accurate when compared with other methods.

Index Terms—license plate detection, multi-features, La*b*, nighttime environment, nonlinear vector quantization

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Cite: Jia Li, "Multi-features-based License Plate Detection in Nighttime Environment," Journal of Software vol. 9, no. 9, pp. 2353-2360, 2014.