Genetic algorithm for best segmentation of gray level images

Abstract EN

Data clustering is collecting the objects that have similar characteristic together for processing purposes.

In this work , genetic algorithm is presented for clustering of images purpose by generating efficient centers of clusters.

The efficiency of generated centers is computed by using Xie-Beni index.

The chromosome represents many centers needed for clustering and its length is proposed between 3 to 10.

The generated centers are used for clustering of different gray levels images.

Quality measures are used to evaluate images after clustering.

Many experiments are used in this system.

In every experiment, genetic algorithm is applied to select the best centers with different number of clusters.

The results with different numbers of clusters showed the efficiency of the proposed method.