License plate detection using neural networks

3Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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. © 2009 Springer Berlin Heidelberg.

Cite

CITATION STYLE

APA

Carrera, L., Mora, M., Gonzalez, J., & Aravena, F. (2009). License plate detection using neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5518 LNCS, pp. 1248–1255). https://doi.org/10.1007/978-3-642-02481-8_186

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free