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EURASIP Journal on Advances in Signal Processing
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Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers

EURASIP Journal on Advances in Signal Processing volume 2004, Article number: 968972 (2004) Cite this article

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.

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Authors and Affiliations

  1. Departamento de Informática, EPS, Universidad Carlos III de Madrid, 28911, Leganés, Madrid, Spain

    Antonio Berlanga, Jesús García Herrero & José M. Molina

  2. GPDS, Departamento Señales, Sistemas y Radiocomunicaciónes, ESTIT, Universidad Politécnica de Madrid, Madrid, 28040, Spain

    Juan A. Besada, Javier I. Portillo & José R. Casar

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  1. Antonio Berlanga
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  2. Juan A. Besada
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  3. Jesús García Herrero
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  4. José M. Molina
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  5. Javier I. Portillo
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  6. José R. Casar
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Corresponding author

Correspondence to Antonio Berlanga.

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Berlanga, A., Besada, J.A., Herrero, J.G. et al. Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers. EURASIP J. Adv. Signal Process. 2004, 968972 (2004). https://doi.org/10.1155/S1110865704312084

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  • DOI: https://doi.org/10.1155/S1110865704312084

Keywords and phrases

  • aircraft recognition
  • evolutionary strategies for OCR
  • statistical pattern classifier
  • image processing