摘要
实现了基于混合蛙跳与模糊C-均值结合的图像分割算法。克服了由于FCM算法易受初始聚类中心和隶属度矩阵的影响而使图像分割效果不理想的缺陷。蛙跳算法(SFLA)是一种全新的后启发式群体优化算法,具有高效的计算性能和优良的全局搜索能力。实验表明:该方法与FPSO结合既提高了图像分割的效率又能得到更好的图像分割效果。
A new image segmentation algorithm in combination with Shuffled frog-leaping algorithm and FCM clustering is proposed,this algorithm could overcome the disfigurement caused by FCM algorithm,which is sensitive to initial clustering center and membership matrix.Shuffled frog-leaping algorithm(SFLA) is a bran-new heuristic colony optimization method,which has effective computing capability and excellent global searching capability.The experimental results indicate that the proposed algorithm could enhance the efficiency of image segmentation,and as compared with the algorithm of FPSO with FCM,could also achieve better image segmentation effect.
出处
《通信技术》
2011年第2期118-119,122,共3页
Communications Technology
关键词
图像分割
混合蛙跳算法
模糊C-均值算法
模糊粒子群算法
全局优化
image segmentation
shuffled frog-leaping algorithm
fuzzy C-mean clustering algorithm
fuzzy particle swarm optimization algorithm
global optimization