Research on the Image Segmentation based on Improved Region Extractions

DOI

10.2991/ncce-18.2018.74How to use a DOI?

Keywords

Image segmentation, region extraction, regional growth method, watershed method.

Abstract

Image segmentation is one of the classic methods of image signal processing. It is widely used in the scientific research, biomedical engineering, military guidance and so on. Based on the region extraction, this paper introduces three typical image segmentation methods: region growth algorithm, watershed algorithm and split and merge method. Computer simulation and the comparison of results show that, Region growth method can be used to break up complex image segmentation, but the cost of time and space are very high, the efficiency is low. By using watershed segmentation, adhesion of the image can be separated, but a watershed method greatly influenced by the noise, easy to excessive segmentation. The effects of split and merge segmentation method and region growth method are similar; there is no significant difference between them.

Copyright

© 2018, 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  - Yi Zhang
AU  - Xiuting Yang
PY  - 2018/05
DA  - 2018/05
TI  - Research on the Image Segmentation based on Improved Region Extractions
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 477
EP  - 481
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.74
DO  - 10.2991/ncce-18.2018.74
ID  - Zhang2018/05
ER  -