Research of Image Segmentation Algorithm Based on Clustering
Authors
Pu Wan, Lisha Wang
Corresponding Author
Pu Wan
Available Online May 2016.
- DOI
- 10.2991/wartia-16.2016.39How to use a DOI?
- Keywords
- image segmentation, clustering, FCM, edge detection, adaptive threshold.
- Abstract
Through the study of existing image segmentation algorithms, this paper improves the standard FCM-based image segmentation algorithm. And according to the principles of effective treatment on neighborhood image noise by mean filtering and median filtering, proposes a new similarity distance calculation method, which gives full consideration to the gray information and neighborhood information of pixels. Experimental results show that this improved algorithm has higher segmentation efficiency, while having a high segmentation accuracy and strong noise immunity.
- 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/).
Cite this article
TY - CONF AU - Pu Wan AU - Lisha Wang PY - 2016/05 DA - 2016/05 TI - Research of Image Segmentation Algorithm Based on Clustering BT - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications PB - Atlantis Press SP - 217 EP - 222 SN - 2352-5401 UR - https://doi.org/10.2991/wartia-16.2016.39 DO - 10.2991/wartia-16.2016.39 ID - Wan2016/05 ER -