A Computation Model for Proximity

This paper designs a computation cluster algorithm based on proximity. Viewing the input elements as points, it is proved that every edge of MST can help to give an unique classification based on the neighbor graph. The method solve the cluster problem by application of the delaunay and Prim algorit...

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Bibliographic Details
Published in2024 IEEE 2nd International Conference on Image Processing and Computer Applications (ICIPCA) pp. 75 - 78
Main Authors Xiaofang, Shao, Ying, Xu, Ning, Guo, Jingru, Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.06.2024
Subjects
Classification algorithms
cluster
Clustering algorithms
Computational complexity
Computational modeling
Computer applications
Euclidean distance
Image edge detection
Image processing
MST
Optimization
proximity
Search problems
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DOI10.1109/ICIPCA61593.2024.10709294

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Summary:This paper designs a computation cluster algorithm based on proximity. Viewing the input elements as points, it is proved that every edge of MST can help to give an unique classification based on the neighbor graph. The method solve the cluster problem by application of the delaunay and Prim algorithm. Experimental results show that the computation results are persistent with human vision perception and provide a distinct classification for the multi cluster centers cluster problem.
DOI:10.1109/ICIPCA61593.2024.10709294