深圳大学学报（理工版）2025，Vol.42Issue(1)：59-67,9.DOI:10.3724/SP.J.1249.2025.01059
基于扩展型活性膜系统的彩色图像分割方法
Color image segmentation method based on extended active membrane system
摘要
Abstract
To overcome the limitations when applying optimization algorithm,such as being prone to local optima and low convergence speed,and enhance performance of extended membrane systems in image processing,an improved northern goshawk optimization(INGO)algorithm,called PINGO,based on an extended active membrane system(P system),is proposed.In PINGO,the northern goshawk optimization(NGO)algorithm serve as the evolution rule in the basic membrane,to evolving objects by updating the goshawk's state,while the improved NGO acts as a local rule for sub-membranes.The system generates or dissolves sub-membranes in the basic membrane according to its characteristics.Communication rules enable information exchange between membranes in order to avoid local optima.The proposed segmentation method PINGO and other comparative algorithms,including seagull optimization algorithm(SOA)、grey wolf optimizer(GWO)and INGO,is evaluated on BSD300 and BSD500 datasets for different images with different number of optimize thresholds.The segmented images of PINGO achieved the best peak signal to noise ratio and 83%best feature similarity maxima,improving segmentation accuracy while maintaining color and texture.Experimental results demonstrate the effectiveness of the proposed method.关键词
图像处理/图像分割/P系统/活性膜结构/北方苍鹰优化算法/进化规则Key words
image processing/image segmentation/P systems/active membrane structure/northern goshawk optimiza-tion algorithm/evolution rule分类
信息技术与安全科学引用本文复制引用
许家昌,郭佳,苏树智..基于扩展型活性膜系统的彩色图像分割方法[J].深圳大学学报（理工版）,2025,42(1):59-67,9.基金项目
National Natural Science Foundation of China(52374155) （52374155）
Anhui University of Science and Technology Medical Special Project(YZ2023H2B008,YZ2023H2A007) 国家自然科学基金资助项目(52374155) （YZ2023H2B008,YZ2023H2A007）
安徽理工大学医学专项培育资助项目(YZ2023H2B008,YZ2023H2 A007) （YZ2023H2B008,YZ2023H2 A007）
