基于IBCC优化算法的多阈值图像分割

Multi-threshold Image Segmentation Based on Improved Bacterial Colony Chemotaxis Optimization Algorithm

图像阈值分割算法中,如何确定最优阈值是关键。使用传统多阈值法对较复杂图像进行分割,存在计算复杂度高、分割速度慢等问题。文章将细菌群体趋药性优化算法和阈值分割算法相结合,并且对细菌群体趋药性算法进行改进,提出了基于改进细菌群体趋药性优化算法的多阈值图像分割算法。实验结果证明,文章提出的算法具有很好的收敛性和稳定性,得到了较好的图像分割效果和图像分割速度。

How to determine the optimal threshold is the key in the image segmentation algorithm. Using traditional multi- threshold method to segment the more complex image,some problems produce such as high computational complexity,slow speed of segmentation.This paper combines bacterial colony chemotaxis optimization algorithm and multi- threshold segmentation algorithm,improves the bacterial colony chemotaxis optimization algorithm. This paper proposes multi- threshold image segmentation based on improved bacterial colony chemotaxis（ IBCC） optimization algorithm. The experimental results show that,the proposed algorithm t has good convergence and stability,and get a good result of image segmentation and image segmentation speed.