Spectral Clustering Based on Multi-scale Stochastic Tree Image Segmentation Algorithm
Chen Yuantao, Zuo Jingwen
Available Online June 2014.
- 10.2991/csss-14.2014.141How to use a DOI?
- spectral clustering; graph, multi-scale stochastic tree, image segmentation, SCMSTIS
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.
- © 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/).
Cite this article
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 -