Machine Learning-Based Image Processing for Ice Concentration during Chukchi and Beaufort Sea Trials
Abstract
:1. Introduction
2. Algorithm for Ice Concentration Calculation
2.1. ROI
2.2. Single Channel Image Conversion & Binarization
2.2.1. RGB Color Space
2.2.2. HSV Color Space
2.2.3. K-Means Clustering
2.2.4. Random Forest
2.3. Camera Calibration
3. Sea Ice Concentration
4. Sea Ice Concentration Using Random Forest Machine Learning
5. Concluding Remarks
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Case 1 | Case 2 | Case 3 | Case 4 | |
---|---|---|---|---|
Hue | 100~140 | 95~145 | 90~150 | 85~155 |
Saturation | 10~255 | 20~255 | 30~255 | 40~255 |
Value | 10~255 | 20~255 | 30~255 | 40~255 |
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Kim, H.; Park, S.; Jeong, S.-Y. Machine Learning-Based Image Processing for Ice Concentration during Chukchi and Beaufort Sea Trials. J. Mar. Sci. Eng. 2023, 11, 2281. https://doi.org/10.3390/jmse11122281
Kim H, Park S, Jeong S-Y. Machine Learning-Based Image Processing for Ice Concentration during Chukchi and Beaufort Sea Trials. Journal of Marine Science and Engineering. 2023; 11(12):2281. https://doi.org/10.3390/jmse11122281
Chicago/Turabian StyleKim, Huichan, Sunho Park, and Seong-Yeob Jeong. 2023. "Machine Learning-Based Image Processing for Ice Concentration during Chukchi and Beaufort Sea Trials" Journal of Marine Science and Engineering 11, no. 12: 2281. https://doi.org/10.3390/jmse11122281
APA StyleKim, H., Park, S., & Jeong, S.-Y. (2023). Machine Learning-Based Image Processing for Ice Concentration during Chukchi and Beaufort Sea Trials. Journal of Marine Science and Engineering, 11(12), 2281. https://doi.org/10.3390/jmse11122281