Determination of optimal threshold of a gray-level image using a quantum inspired genetic algorithm with interference based on a random map model

In this article, a variant quantum inspired genetic algorithm for the determination of the optimal threshold of gray-level images is presented. The proposed algorithm initiates with a population of randomly superposed trial solutions in the form of quantum bits. Subsequently, some deterministic nonlinear point transformations are applied on these solutions to generate randomly interfered solutions. Quantum inspired crossover and mutation are then applied on the resultant solution space. Finally, a quantum measurement operation leads to the determination of the optimal solution. Applications of the proposed method for the determination of the optimal thresholds of real life gray-level images are demonstrated.