Number Plate Detection with a Multi-Convolutional Neural Network Approach with Optical Character Recognition for Mobile Devices

被引:8
作者
Gerber, Christian [1 ]
Chung, Mokdong [2 ,3 ]
机构
[1] Pukyong Natl Univ, Dept Comp Engn, Busan, South Korea
[2] Pusan Univ Foreign Studies, Pusan, South Korea
[3] Pukyong Natl Univ, Busan, South Korea
来源
JOURNAL OF INFORMATION PROCESSING SYSTEMS | 2016年 / 12卷 / 01期
关键词
Convolutional Neural Network; Number Plate Detection; OCR;
D O I
10.3745/JIPS.04.0022
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
In this paper, we propose a method to achieve improved number plate detection for mobile devices by applying a multiple convolutional neural network (CNN) approach. First, we processed supervised CNN-verified car detection and then we applied the detected car regions to the next supervised CNN-verifier for number plate detection. In the final step, the detected number plate regions were verified through optical character recognition by another CNN-verifier. Since mobile devices are limited in computation power, we are proposing a fast method to recognize number plates. We expect for it to be used in the field of intelligent transportation systems.
引用
收藏
页码:100 / 108
页数:9
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