Image segmentation using quantum genetic algorithms

Abstract

On one hand, image segmentation is a low-level processing task which consists in partitioning an image into homogeneous regions. It can be seen as being a combinatorial optimization problem. In fact, considering the huge amount of information that an image carries, it is impossible to find the best segmentation. On the other hand, quantum genetic algorithms are characterized by their high diversity, and by a good balance between global and local search. In this paper, we present a quantum genetic algorithm for image segmentation