License Plate Detection and Recognition Using CRAFT and LSTM

被引:0
|
作者
Anh Kiet Huynh [1 ,2 ]
Tan Duy Le [1 ,2 ]
Kha-Tu Huynh [1 ,2 ]
机构
[1] Int Univ, Sch Comp Sci & Engn, Ho Chi Minh City, Vietnam
[2] Vietnam Natl Univ, Ho Chi Minh City, Vietnam
来源
INTELLIGENT DISTRIBUTED COMPUTING XV, IDC 2022 | 2023年 / 1089卷
关键词
CRAFT; License Plate Detection; License Plate Recognition; deep neural network;
D O I
10.1007/978-3-031-29104-3_31
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This work proposes a solution for developing a license plate detection and recognition system (LPDR). In the first stage, the poly region of the license plate's word line(s) can be detected by Character-Region Awareness For Text Detection (CRAFT). Specifically, the text line of the one-line license plate and two lines of the multi-line license plate can be detected effectively. Secondly, each region proposed as a plate number region by CRAFT will be passed to Mobilenet architecture to extract features. Finally, these features will be fed to Bi long short-term memory (Bi-LSTM) architecture with Connectionist Temporal Classification to predict output text in each input region. By applying this solution, the problem of multi-line license plates can be appropriately handled.
引用
收藏
页码:287 / 296
页数:10
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