License plate detection based on fully convolutional networks

被引:11
作者
Xiang, Han [1 ,2 ]
Yuan, Yule [3 ]
Zhao, Yong [1 ,4 ]
Fu, Zufeng [1 ,5 ]
机构
[1] Guizhou Univ, Sch Comp Sci & Technol, Guiyang, Guizhou, Peoples R China
[2] Guangdong Med Univ, Sch Informat & Engn, Dongguan, Peoples R China
[3] Shenzhen Technol Univ, Sch Big Data & Internet, Shenzhen, Peoples R China
[4] Peking Univ, Shenzhen Grad Sch, Sch Elect & Comp Engn, Shenzhen, Peoples R China
[5] Anshun Coll, Sch Elect & Informat Engn, Anshun, Peoples R China
关键词
license plate detection; fully convolutional networks; multiscale hierarchical features; enhanced loss layer; RECOGNITION;
D O I
10.1117/1.JEI.26.5.053027
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fully convolutional networks (FCNs) have shown outstanding performance in image semantic segmentation, which is the key work in license plate detection (LPD). An FCN architecture for LPD is presented. First, a multiscale hierarchical network structure is used to combine multiscale and multilevel features produced by FCN. Then, an enhanced loss structure that contains three loss layers is defined to emphasize the license plates in images. Finally, the FCN generates prediction maps that directly show the location of license plates. Experiments show that our approach is more accurate than many state-of-the-art methods. (C) 2017 SPIE and IS&T
引用
收藏
页数:7
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