Parallel nearest neighbour clustering algorithm (PNNCA) for segmenting retinal blood vessels

被引：0
|
作者：
Salem, Sameh A. [1 ]
Nandi, Asoke K. [1 ]
机构：
[1] Univ Liverpool, Dept Elect & Elect Engn, Signal Proc & Commun Grp, Liverpool L69 3GJ, Merseyside, England
来源：
PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED COMPUTING AND NETWORKS | 2007年
关键词：
parallel processing; retinal image segmentation; data clustering; unsupervised classification; computer clusters;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the design and implementation of a recently developed clustering algorithm NNCA [1], Nearest Neighhour Clustering Algorithm, is proposed in conjunction with a Fast K Nearest Neighbour (FKNN) strategy for further reduction in processing time. The parallel algorithm (PNNCA) has the ability to cluster pixels of retinal images into those belonging to blood vessels and others not belonging to blood vessels in a reasonable time.
引用
收藏
页码：263 / +
页数：2
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