Oil Spill Image Segmentation Based on Fuzzy C-means Algorithm
- https://doi.org/10.2991/csic-15.2015.98How to use a DOI?
- Oil aerial image, Color model, YCbCr color space, Fuzzy C-means Algorithm
Oil spill may cause serious pollution of the marine environment. Unmanned aerial vehicles remote sensing system can be used to monitor oil spill conditions. In order to identify the oil spill area on aerial image accurately, the first step is oil spill region segmentation. The paper presents an image segmentation method of oil spill area based on fuzzy C-means Algorithm. Firstly, according to the color characteristics of the oil, the paper selects YCbCr color space as the feature space. Then, the paper uses fuzzy clustering algorithm to divide the color feature space. Finally, according to oil color model, the paper selects clustering result as the segmentation results of oil spill area. Experiment show that the proposed algorithm’s accuracy for oil region segmentation of calibration attain to 95 percent.
- © 2015, 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 - Guangmin Sun AU - Haocong Ma AU - Dequn Zhao AU - Fan Zhang AU - Linan Jia AU - Junling Sun PY - 2015/07 DA - 2015/07 TI - Oil Spill Image Segmentation Based on Fuzzy C-means Algorithm BT - Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication PB - Atlantis Press SP - 406 EP - 409 SN - 2352-538X UR - https://doi.org/10.2991/csic-15.2015.98 DO - https://doi.org/10.2991/csic-15.2015.98 ID - Sun2015/07 ER -