Abstract
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.
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Acknowledgements
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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Alvarado-Cervantes, R., Felipe-Riveron, E.M., Khartchenko, V., Pogrebnyak, O., Alvarado-Martínez, R. (2018). Behavior of the CIE L*a*b* Color Space in the Detection of Saturation Variations During Color Image Segmentation. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Computational Intelligence. MICAI 2017. Lecture Notes in Computer Science(), vol 10633. Springer, Cham. https://doi.org/10.1007/978-3-030-02840-4_19
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