Efficient Image Segmentation Method Based on Sparse Subspace Clustering

DOI

10.2991/meici-16.2016.111How to use a DOI?

Keywords

Subspace clustering; Image segmentation; Sparse metric; Sparse representation

Abstract

A novel image segmentation method based on weighted sparse subspace clustering is presented. By choosing the l2,1 norm as sparse metric, feature datas are kept uniformly within the same subspace;By constraints of weighted sparse metric, feature datas are kept sparse within different subspace.Experiments show that the proposed weighted sparse subspace clustering method can obtain higher clustering accuracy than the state of old methods.

Copyright

© 2016, 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  - Jianping Huang
PY  - 2016/09
DA  - 2016/09
TI  - Efficient Image Segmentation Method Based on Sparse Subspace Clustering
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 530
EP  - 533
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.111
DO  - 10.2991/meici-16.2016.111
ID  - Huang2016/09
ER  -