混合量子粒子群图像分割算法IS-MQPS

基于群智能的图像分割技术因其与人类视觉机理相符合,受到人们重视。但是,现有群体模型存在的对参数取值敏感和易收敛于局部极值等问题,制约了群智能技术在复杂图像分割中的应用。首先定义了基于群智能图像分割的抽象模型,然后将通用量子粒子模型GQPM引进图像分割,提出了混合量子粒子群图像分割算法IS-MQPS。IS-MQPS算法以量子粒子携带灰度和坐标信息,以纠缠量子态定义群体行为规则,以混合量子粒子群的自组织聚类实现图像分割。实验表明,IS-MQPS算法具有对噪声不敏感、分割区域意义明确等优点,可应用于复杂图像分割。

A novel image segmentation algorithm based on mixed quantum particle swarm

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.