Yager's measure based fuzzy divergence for microscopic color image segmentation

This paper addressed the development of a novel segmentation method for color image segmentation using fuzzy divergence metric based on Yager's measure. This measure is considered here to calculate the divergence value as threshold in each red, green and blue (RGB) color plane. Afterwards, three segmented masks obtained in three color planes are combined to obtain the final segmented region of interest. This method has successfully been applied to microscopic images of peripheral blood smears in recognizing leukocyte's nuclei and malaria infected erythrocytes. These results are obtained and compared with the segmentation results of fuzzy divergence using Shannon's entropy and Renyi's entropy.