Dan Liu1,3, Yajuan Wu1, Yuxin He2, Lu Qin2, Bochuan Zheng2,3,*
Computer Systems Science and Engineering, Vol.36, No.1, pp. 145-156, 2021, DOI:10.32604/csse.2021.014646
Abstract Multi-license plate detection in complex scenes is still a challenging task because of multiple vehicle license plates with different sizes and classes in the images having complex background. The edge features of high-density distribution and the high curvature features of stroke turning of Chinese character are important signs to distinguish Chinese license plate from other objects. To accurately detect multiple vehicle license plates with different sizes and classes in complex scenes, a multi-object detection of Chinese license plate method based on improved YOLOv3 network was proposed in this research. The improvements include replacing the residual block of the YOLOv3 backbone… More >
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