Open Access

Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers

  • Antonio Berlanga1Email author,
  • Juan A. Besada2,
  • Jesús García Herrero1,
  • José M. Molina1,
  • Javier I. Portillo2 and
  • José R. Casar2
EURASIP Journal on Advances in Signal Processing20042004:968972

DOI: 10.1155/S1110865704312084

Received: 18 December 2002

Published: 8 July 2004

Abstract

The design of statistical classification systems for optical character recognition (OCR) is a cumbersome task. This paper proposes a method using evolutionary strategies (ES) to evolve and upgrade the set of parameters in an OCR system. This OCR is applied to identify the tail number of aircrafts moving on the airport. The proposed approach is discussed and some results are obtained using a benchmark data set. This research demonstrates the successful application of ES to a difficult, noisy, and real-world problem.

Keywords and phrases

aircraft recognition evolutionary strategies for OCR statistical pattern classifier image processing

Authors’ Affiliations

(1)
Departamento de Informática, EPS, Universidad Carlos III de Madrid
(2)
GPDS, Departamento Señales, Sistemas y Radiocomunicaciónes, ESTIT, Universidad Politécnica de Madrid

Copyright

© Berlanga et al. 2004