License Plate Detection Using Neural Networks

被引：0

作者：

Carrera, Luis ^{[1
]}

Mora, Marco ^{[1
]}

Gonzalez, Jose ^{[2
]}

Aravena, Francisco ^{[2
]}

机构：

[1] Catholic Univ Maule, Dept Comp Sci, Image Proc Res Grp, Casilla 617, Talca, Chile

[2] TUTELKAN, Talca, Chile

来源：

DISTRIBUTED COMPUTING, ARTIFICIAL INTELLIGENCE, BIOINFORMATICS, SOFT COMPUTING, AND AMBIENT ASSISTED LIVING, PT II, PROCEEDINGS | 2009年 / 5518卷

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：

This work presents a new method for license plate detection using neural networks in gray scale images. The method proposes a multiple classification strategy based on a Multilayer Perceptron. It consists of many classifications of one image using several shifted window grids. If a pixel belongs or not to the licence plate is determined by the most frequent answer given by the different classifications. The result becomes more precise by means of morphological operations and heuristic rules related to shape and size of the license plate zone. The whole method detects the license plates precisely with a low error rate under non-controlled environments.

引用

页码：1248 / +

页数：3

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