Automatic clustering using quantum-based multi-objective emperor penguin optimizer and its applications to image segmentation

In this study, a novel quantum-based multi-objective is proposed using Schrödinger equations. The two new operations namely weighted cluster centroid computation and threshold setting are also introduced to refine cluster centroids. A novel fitness function strategy is also proposed for efficient searching. The proposed technique is compared with various well-known approaches. Experimental outcomes show that the proposed quantum approach outperforms other existing approaches.