基于直方图相关性约束的快速多阈值FCM图像分割算法

针对传统的模糊C均值(FCM)聚类算法在样本数和特征数较多时,运算较为复杂以及耗时较多的问题,本文提出了一种采用直方图的相关性作为约束采样率的快速多阈值FCM分割方法,控制图像失真,使得需要运算的数据量减少,以获得较快的分割速度.由于借助了基于模糊集的图像分割技术--模糊C均值算法实现多阈值图像分割,考虑到了每个像素对...

Fast Multi-Threshold Fuzzy C-Means Image Segmentation Based on Histogram Correlation Constraints

The traditional fuzzy C-means(FCM) clustering algorithm has some problems,such as massive calculation and slow operation speed,especially the large amount of data.A fast multi-thresholds FCM algorithm based on histogram correlation constraints is proposed to control the image distortion due to resampling.Because of the amount of data in the operation has been reduced,the segmentation speed turns faster.In this paper,image segmentation uses the fuzzy techniques of the fuzzy C-Means(FCM) algorithm which considers each pixel for the cluster center membership.FCM can achieve multi-threshold image segmentation which features good applicability.The experimental results which make it valuable on application shows that the proposed algorithm preserves the effect and costs only 1.4% the time of the traditional FCM.