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.
CITATION STYLE
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
Mendeley helps you to discover research relevant for your work.