融合边缘流和模糊区域聚类的岩心图像分割  

Core image segmentation method by combining edgeflow and fuzzy region clustering

作　　者：曹华美[1] 吴晓红[1] 罗代升[1] 

机构地区：[1]四川大学电子信息学院,成都610064

出　　处：《计算机工程与应用》2013年第6期187-189,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(No.60972130);中央高校基本科研业务费专项资金资助(No.2009SCU11009);四川省科技支撑计划(No.10ZC0968)

摘　　要：提出一种融合边缘流和模糊区域聚类的图像分割方法。选用高精度的灰度边缘流对图像进行分割,得到边缘流的矢量方向和边缘能量,通过曲线演化得到初始分割图像;在初始分割产生的小区域上,综合小区域的色彩空间特征和图像空间特征,进行了模糊区域聚类;将聚类结果用于修正初始分割图像,去除过分割。实验表明,在对岩心图像的分割中,该方法能取得良好的效果。An image segmentation method which combines edgeflow and fuzzy region clustering is put forward. An image is segmented by high precision of gray edgeflow to obtain the vector directions and edge energies of the edgeflow. The vector direc- tions and edge energies are then used to get the initial segmented image through curve evolution. The small areas generated by the initial segmentation are clustered by using the joint distribution of color space and image space. The results of the clustering are used to correct the initial segmented image to remove over-segmentation. The experimental results show that this method can obtain good effect in core image segmentation.

关 键 词：边缘流 聚类 图像分割 曲线演化 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]