A Coral-Color Analysis System for Observing Environmental Situation and Change with K-means Clustering and Semantic Classification
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Abstract
The impact of rapid ocean warming due to climate change poses a serious risk to the survival of coral reefs. Our motivation is to promote healthy reefs by engaging the global community in monitoring coral health and coral bleaching with Global Environmental Semantic Computing System. We have already proposed a new "Coral-health-level interpretation method" with coral image, coral-chart, and semantic computing. Based on this method, this paper presents an actual implementation of this method with an advanced Coral-Color Analysis System for Observing Environmental Situation and Change. This paper proposes to apply K-means clustering to HSV color systems and Semantic Classification for Coral-health levels with high precision. We clarify our method, system's feasibility, and effectiveness by showing several experimental results on Coral-health levels and color semantic distance between coral and coral health chart colors.
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