License plate recognition system using hybrid neural networks

被引：0
|
作者：
Seetharaman, V [1 ]
Nathan, VSL [1 ]
Sathyakhala, A [1 ]
Sunder, P [1 ]
机构：
[1] Sri Ramakrishna Engn Coll, Dept Comp Sci, Coimbatore, Tamil Nadu, India
来源：
NAFIPS 2004: ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1AND 2: FUZZY SETS IN THE HEART OF THE CANADIAN ROCKIES | 2004年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
License plate recognition is one of the machine vision problem which has a wide range of practical applications. Various methodologies have been suggested with varying efficiencies. In this paper we propose an ASIC implementation of a new methodology which uses a hybrid neural network in conjunction with the weight based density map technique for the license plate localization. The combination of the two techniques, that have already been used individually, has produced higher recognition rates. Further the ASIC implementation means that the time complexity of the methodology can be completely ignored. The system design and the experimental results of the system have been discussed briefly.
引用
收藏
页码：363 / 366
页数：4
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