Resumen

OCHOA-MONTIEL, R. et al. Segmentation of Microscopic Images with NSGA-II. Comp. y Sist. [online]. 2018, vol.22, n.2, pp.387-412.  Epub 21-Ene-2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-22-2-2944.

This paper addresses the problem of multiobjective segmentation on microscopic images by using the evolutionary algorithm NSGA-II. Two objective functions are used at the optimization process: Otsu’s inter-class variance and Shannon’s entropy. A set of 71 images of blood cells are used. From this set, three categories of images are generated: with and without preprocessing, and images with Gaussian noise. Experimental results shown that the use of evolutionary multiobjective techniques like NSGA-II, give satisfactory results in the segmentation for more than one category of images.

Palabras llave : Segmentation; multiobjective evolutionary optimization; microscopic images.