https://store-images.s-microsoft.com/image/apps.65179.a03b989a-968d-4ba2-9241-a0781b7d7e80.c5bf9f46-210a-46c9-ae9b-f4519851a725.2caceeca-02c8-46f8-ba3a-250de8930d38
Water Automatic River Segmentation
At Mind SpA
Water Automatic River Segmentation
At Mind SpA
Water Automatic River Segmentation
At Mind SpA
Automatic Segmentation of Water Bodies using RGB Data: A Physically Based Approach
Automatically segment water extent using a physically based model which integrates reflectance of the water surface with spectral and quantum interpretation of light. The algorithm was tested on 27 rivers and compared to manually-based delimitation, with a resulting robust segmentation procedure. Quantified errors were RMSE = 11.91 (m2) for surface area, RMSE = 12.25 (m) for perimeter, and RMSE in x: 52 (px), RMSE in y: 93 (px) for centroid location. Processing time was faster for automatic segmentation than manual delimitation, with a time reduction of 40% (case-by-case analysis) and 65% (using all case studies together in one run).
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The Scientific Principleshttps://store-images.s-microsoft.com/image/apps.8675.a03b989a-968d-4ba2-9241-a0781b7d7e80.5dad9ec1-f431-4412-94b4-3b373fcc174c.4bdc8fb1-565c-4c2d-8dff-f8dd8a9d2600
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https://store-images.s-microsoft.com/image/apps.47907.a03b989a-968d-4ba2-9241-a0781b7d7e80.5dad9ec1-f431-4412-94b4-3b373fcc174c.5d205020-cb2a-4786-9523-26dcccdc9c61
https://store-images.s-microsoft.com/image/apps.49657.a03b989a-968d-4ba2-9241-a0781b7d7e80.5dad9ec1-f431-4412-94b4-3b373fcc174c.b658a2e9-0bf7-4ecc-82b0-5f521b58ca41
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https://store-images.s-microsoft.com/image/apps.44965.a03b989a-968d-4ba2-9241-a0781b7d7e80.5dad9ec1-f431-4412-94b4-3b373fcc174c.2e415bee-e94b-41c8-8ad6-b4f662773fd5