Spectral Clustering Based on Multi-scale Stochastic Tree Image Segmentation Algorithm

DOI

10.2991/csss-14.2014.141How to use a DOI?

Keywords

spectral clustering; graph, multi-scale stochastic tree, image segmentation, SCMSTIS

Abstract

For spectral clustering is applied to image segmentation is difficult to calculate the spectral weight matrix of the actual problem, we have defined the pixel distance between the point and the class is given a sampling theorem, the design of a hierarchical image segmentation algorithm in the use of this algorithm for image segmentation. By adjusting the scaling factor to merge or split a large class of smaller classes, so the image segmentation both randomness but also has multi-scale feature, called spectral clustering based on multi-scale stochastic tree image segmentation (SCMSTIS). The experimental results show that the algorithm is effective.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chen Yuantao
AU  - Zuo Jingwen
PY  - 2014/06
DA  - 2014/06
TI  - Spectral Clustering Based on Multi-scale Stochastic Tree Image Segmentation Algorithm
BT  - Proceedings of the 3rd International Conference on Computer Science and Service System
PB  - Atlantis Press
SP  - 605
EP  - 608
SN  - 1951-6851
UR  - https://doi.org/10.2991/csss-14.2014.141
DO  - 10.2991/csss-14.2014.141
ID  - Yuantao2014/06
ER  -