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

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

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 mo...

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Bibliographic Details
Main Authors: Antonio Berlanga, Juan A. Besada, Jesús García Herrero, José M. Molina, Javier I. Portillo, José R. Casar
Format: Article
Language:English
Published: SpringerOpen 2004-07-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
aircraft recognition
evolutionary strategies for OCR
statistical pattern classifier
image processing.
Online Access:http://dx.doi.org/10.1155/S1110865704312084
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spelling doaj-02d3a3d4042a4311bcfb922235ea1b912020-11-25T00:32:48ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802004-07-01200481125113410.1155/S1687617204312084Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail NumbersAntonio BerlangaJuan A. BesadaJesús García HerreroJosé M. MolinaJavier I. PortilloJosé R. CasarThe 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.http://dx.doi.org/10.1155/S1110865704312084aircraft recognitionevolutionary strategies for OCRstatistical pattern classifierimage processing.
collection DOAJ
language English
format Article
sources DOAJ
author Antonio Berlanga
Juan A. Besada
Jesús García Herrero
José M. Molina
Javier I. Portillo
José R. Casar
spellingShingle Antonio Berlanga
Juan A. Besada
Jesús García Herrero
José M. Molina
Javier I. Portillo
José R. Casar
Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
EURASIP Journal on Advances in Signal Processing
aircraft recognition
evolutionary strategies for OCR
statistical pattern classifier
image processing.
author_facet Antonio Berlanga
Juan A. Besada
Jesús García Herrero
José M. Molina
Javier I. Portillo
José R. Casar
author_sort Antonio Berlanga
title Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
title_short Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
title_full Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
title_fullStr Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
title_full_unstemmed Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers
title_sort optimizing statistical character recognition using evolutionary strategies to recognize aircraft tail numbers
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2004-07-01
description 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.
topic aircraft recognition
evolutionary strategies for OCR
statistical pattern classifier
image processing.
url http://dx.doi.org/10.1155/S1110865704312084
work_keys_str_mv AT antonioberlanga optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
AT juanabesada optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
AT jesusgarciaherrero optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
AT josemmolina optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
AT javieriportillo optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
AT josercasar optimizingstatisticalcharacterrecognitionusingevolutionarystrategiestorecognizeaircrafttailnumbers
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