Behavior of the CIE L*a*b* Color Space in the Detection of Saturation Variations During Color Image Segmentation

  • Rodolfo Alvarado-Cervantes
  • Edgardo M. Felipe-Riveron
  • Vladislav Khartchenko
  • Oleksiy Pogrebnyak
  • Rodolfo Alvarado-Martínez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10633)


In this paper, a study of the behavior of the CIE L*a*b* color space to detect subtle changes of saturation during image segmentation is presented. It was performed a comparative study of some basic segmentation techniques implemented in the L*a*b*, RGB color space and in a modified HSI color space using a recently published adaptive color similarity function. In the CIE L*a*b* color space we have studied the behavior of: (1) the Euclidean metric of a* and b* color components rejecting L* and (2) a probabilistic approach on a* and b*. From the results it was obtained that the CIE L*a*b* color space is not adequate to distinguish subtle changes of color saturation under illumination variations. In some high saturated color regions the CIE L*a*b* is not useful to distinguish saturation variations at all. It can be observed that the CIE L*a*b* has better performance than the RGB color space in low saturated regions but it has worse performance in most high saturated color regions; all high saturation regions are very sensitive to changes in illumination and a minimum change causes failures during segmentation. The improvement in quality of the recently published color segmentation technique to distinguish subtle saturation variations is substantially significant.


CIELAB L*a*b* color space Color metrics Color categorization Color image segmentation Color segmentation evaluation Synthetic color image generation 



The authors of this paper wish to thank to the Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional (IPN); México; Secretaría de Investigación y Posgrado (SIP), México; Centro de Investigaciones Teóricas, Facultad de Estudios Superiores Cuautitlán (FES-C), Universidad Nacional Autónoma de México (UNAM), Proyectos PAPIIT IN113316; PAPIIT IN112913 and PIAPIVC06, UNAM; Departamento de Investigación en Electrónica de Control e Inteligencia Artificial, Industrias Electrónicas Ateramex, S.A. de C.V., for their economic support to this work.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Rodolfo Alvarado-Cervantes
    • 1
    • 2
    • 3
  • Edgardo M. Felipe-Riveron
    • 1
  • Vladislav Khartchenko
    • 2
  • Oleksiy Pogrebnyak
    • 1
  • Rodolfo Alvarado-Martínez
    • 3
  1. 1.Centro de Investigación En Computación, Instituto Politécnico NacionalMexico CityMexico
  2. 2.Centro de Investigaciones Teóricas, Facultad de Estudios Superiores Cuautitlán, Universidad Nacional Autónoma de MéxicoCuautitlán IzcalliMexico
  3. 3.Departamento de Investigación En Electrónica de Control E Inteligencia Artificial, Industrias Electrónicas Ateramex, S.a. de C.VCuautitlán IzcalliMexico

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