Intuitionistic fuzzy sets applied to color image processing

Segmentation of color images is a challenge which is in constant development as they provide more information than a gray-scale image. In particular, the analysis of biomedical images is specially helpful for many purposes. In this work, a method to segment leukocytes is presented. This method is based on the combination of the use of RGB color space, intuitionistic fuzzy sets and K-means. The results show a good performance of the proposed method achieving the segmentation of the objects of interest.

[1]  J. Serra,et al.  MATHEMATICAL MORPHOLOGY IN COLOR SPACES APPLIED TO THE ANALYSIS OF CARTOGRAPHIC IMAGES , 2003 .

[2]  Humberto Bustince,et al.  Colour Image Segmentation using A-IFSs , 2009, IFSA/EUSFLAT Conf..

[3]  Pagavathigounder Balasubramaniam,et al.  A new thresholding technique based on fuzzy set as an application to leukocyte nucleus segmentation , 2016, Comput. Methods Programs Biomed..

[4]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[5]  A. K. Ray,et al.  A new measure using intuitionistic fuzzy set theory and its application to edge detection , 2008, Appl. Soft Comput..

[6]  Tamalika Chaira,et al.  Accurate segmentation of leukocyte in blood cell images using Atanassov's intuitionistic fuzzy and interval Type II fuzzy set theory. , 2014, Micron.

[7]  Nikhil R. Pal,et al.  Divergence Measures for Intuitionistic Fuzzy Sets , 2015, IEEE Transactions on Fuzzy Systems.

[8]  Isabelle Bloch,et al.  Fuzzy mathematical morphologies: A comparative study , 1995, Pattern Recognit..

[9]  Xiaomei Li,et al.  White Blood Cell Segmentation by Color-Space-Based K-Means Clustering , 2014, Sensors.

[10]  Nicolas Vandenbroucke,et al.  Color Spaces and Image Segmentation , 2008 .

[11]  Lola X. Bautista Rozo,et al.  Automatic Leukocyte Image Segmentation: A review , 2015, 2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA).

[12]  Tamalika Chaira.  Intuitionistic fuzzy color clustering of human cell images on different color models , 2012, J. Intell. Fuzzy Syst..

[13]  Zuoyong Li,et al.  LeukocyteMask: An automated localization and segmentation method for leukocyte in blood smear images using deep neural networks , 2019, Journal of biophotonics.

[14]  Thomas de Quincey.  [C] , 2000, The Works of Thomas De Quincey, Vol. 1: Writings, 1799–1820.

[15]  Salim Arslan,et al.  A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images , 2014, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[16]  M. Sugeno.  FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .

[17]  Xin Zheng,et al.  Fast and robust segmentation of white blood cell images by self-supervised learning. , 2018, Micron.

[18]  Amit Konar,et al.  Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding. , 2014, Micron.

[19]  Virginia L. Ballarin,et al.  Intuitionistic fuzzy set and fuzzy mathematical morphology applied to color leukocytes segmentation , 2019, Signal, Image and Video Processing.

[20]  Jae-Yeal Nam,et al.  Automatic white blood cell segmentation using stepwise merging rules and gradient vector flow snake. , 2011, Micron.

[21]  Humberto Bustince,et al.  Intuitionistic fuzzy generators Application to intuitionistic fuzzy complementation , 2000, Fuzzy Sets Syst..

[22]  Donald P. Greenberg,et al.  Color spaces for computer graphics , 1978, SIGGRAPH.

[23]  Mihai Ivanovici,et al.  Probabilistic pseudo-morphology for grayscale and color images , 2014, Pattern Recognit..