Using Genetic Algorithm in Image Clustering


The aim of this work is to optimize gray scale image clustering using twotraditional methods, these are thresholding technique and genetic algorithm (GA).The clustering optimization is achieved by applying three features (gray value,distance, gray connection) based thresholding technique and genetic algorithm. Inthis work clustering optimization includes segmenting the image to find regionsthat represent objects or meaningful parts of objects depending on the abovementioned three features which base on gray value of image and two standardmathematical theories these are chessboard distance and breshenham's algorithm.There are many recent researches in this subject some of them depending on grayvalue feature to clustering images, but in this research depended on three featureswhich is making the clustering operation more accuracy.