Abstract:

Image segmentation technology based on swarm intelligence has been paid more and more attentions due to its consistency with human visual mechanism. However, many existing swarm models are sensitive to parameter values and easy to converge to the local minimum, which restricts the application of swarm intelligence in complex image segmentation. In the paper, we define the abstract model of image segmentation based on swarm intelligence firstly, and then propose a novel image segmentation algorithm based on mixed quantum particle swarm (ISMQPS) by introducing the eneralized quantum particle model (GQPM) into image segmentation. ISMQPS contains three key parts: defining the quantum particle by pixel's grey value and position value, defining the swarm action rule by entangled quantum state, and realizing image segmentation by selforganization clustering of mixed quantum particle swarm. Experiments show that ISMQPS is insensitive to noise, has good segmentation effect, and can be used in complex image segmentation.

Key words:  image segmentation;swarm intelligence;generalized quantum particle model;mixed quantum particle swarm