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Comparative of Effectiveness When Classifying Colors Using RGB Image Representation with PSO with Time Decreasing Inertial Coefficient and GA Algorithms as Classifiers

  • Martín MontesEmail author
  • Alejandro Padilla
  • Juana Canul
  • Julio Ponce
  • Alberto Ochoa
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 749)

Abstract

Several transformations from basic RGB representation in digital color images have been developed, CIELab and HSV are commonly applied for color classification, because in this colors spaces there is only a single value adjusted for a specific color detection, nevertheless this transformation require high computational power for transforming every single pixel in a picture. Artificial intelligence (AI) algorithms have been applied before for color classification, but using indistinctly RGB, CIELab and HSV representations among other color transformations even when this transformation can be omitted since they were developed for color classification without AI algorithms. In this paper, is proposed an algorithm for optimizing line equations obtained from three spaces directly generated as a dimensional reduction of the RGB space and we show the comparison of the achieved results optimizing these equations with a GA and PSO algorithms.

Keywords

Color classification PSO GA Color spaces 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Martín Montes
    • 1
    Email author
  • Alejandro Padilla
    • 2
  • Juana Canul
    • 3
  • Julio Ponce
    • 2
  • Alberto Ochoa
    • 4
  1. 1.Universidad Politécnica de AguascalientesAguascalientesMexico
  2. 2.Universidad Autónoma de AguascalientesAguascalientesMexico
  3. 3.Universidad Juárez Autónoma de TabascoVillahermosaMexico
  4. 4.Universidad Autónoma de Ciudad JuárezCiudad JuárezMexico

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