基于混沌微粒群和二维Otsu法的图像快速分割

基金项目:

四川省科技攻关资助项目(04GG010-004-1)

详细信息

Fast Image Segmentation Based on Chaotic Particle Swarm and Two-Dimension Otsu Method

1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China;
2. Institute of Applied Electrinics AEP, Mianyang 621900, China

摘要: 为了解决二维Otsu法在求取最佳阈值时存在计算量大,及微粒群算法容易陷入局部最优且速度较慢等问题,提出一种将混沌微粒群优化算法和二维Otsu法相结合的图像分割方法。利用混沌微粒群优化算法,实现二维阈值向量的快速全局搜索。实验证明,该算法对复杂图像具有良好的分割效果和较强的实时处理能力。
- 图像分割 /
- 微粒群 /
- 混沌优化 /
- 二维Otsu法
Abstract: The computation burden of finding optimal threshold vector was very large for 2-D Otsu method,and the PSO algorithm can easily lead to local optimal issues,In order to solve these problems,a feature image segmentation was presented based on the CPSO algorithm and 2-D Otsu image segmentation method.CPSO algorithm was used to realize the rapid global optimization and search for the optimal threshold value of two-dimensional vector.Simulation results show that the proposed algorithm has good results to image which is similar to the core and a strong real-time processing capability.
- image segmentation /
- particle swarm /
- chaotic optimization /
- 2-D Otsu