Lung Cancer Detection Using Image Segmentation by means of Various Evolutionary Algorithms

Algorithm 5

k-Median clustering.

(1)	Select the random cluster centers. Let the number of cluster centers be “C.”
(2)	Calculate the Euclidean distance.
(3)	Take each and every pixel and assign them into the appropriate cluster if the Euclidean distance is minimum between the cluster and pixel.
(4)	Once the segregation is completed for all the pixels, recalculate the new cluster center using the median value instead of using a squared formula.
(5)	Repeat the steps from 2 to 4 for some number of iterations or until a certain condition is encountered.