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基于模糊率的FCM自适应图像分割方法
引用本文:龚劬,权佳成.基于模糊率的FCM自适应图像分割方法[J].计算机工程,2011,37(10):202-203.
作者姓名:龚劬  权佳成
作者单位:重庆大学数学与统计学院,重庆,400044
基金项目:国家自然科学基金资助项目
摘    要:提出一种基于模糊率的模糊C均值自适应图像分割方法。该方法根据波谷波峰梯度检测法自动确定模糊聚类数目,利用模糊阈值法快速确定较为准确的初始聚类中心,建立包含特征信息和空间信息的新目标函数,实现图像的自动分割。实验结果表明,该方法的分割速度快、精度较高,具有较强的鲁棒性。

关 键 词:模糊聚类  图像分割  模糊阈值  邻域信息  鲁棒性

Adaptive FCM Method for Image Segmentation Based on Fuzziness Rate
GONG Qu,QUAN Jia-cheng.Adaptive FCM Method for Image Segmentation Based on Fuzziness Rate[J].Computer Engineering,2011,37(10):202-203.
Authors:GONG Qu  QUAN Jia-cheng
Affiliation:(College of Mathematics and Statistics,Chongqing University,Chongqing 400044,China)
Abstract:An adaptive Fuzzy C-Means(FCM) method for image segmentation based on fuzziness rate is proposed.It automatically determines the proper number of fuzzy clustering by utilizing the gradient detection method of wave trough and peak.Accurate original cluster centers are acquired by utilizing fuzzy threshold method.A novel objective function is established which contains feature information and spatial information.Experimental results show that the method has fast segmentation speed and high segmentation accuracy,and has stronger robustness.
Keywords:fuzzy clustering  image segmentation  fuzzy threshold  neighbor information  robustness
本文献已被 CNKI 维普 万方数据 等数据库收录!
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