Features extraction from carbonate modern platforms satellite imagery using Computer Vision.

Firstly, a Python code load massive satellite imagery from a specific folder RGB format, then each raw coral reef image is resized, converted from RGB band to gray, smoothed, and binarized using Open Computer Vision Library available in Python 3.0. The coral reef edge information contains very promi...

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Bibliographic Details
Published in:Petroleum & Coal Vol. 62; no. 3; pp. 899 - 907
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Format: Article
Published: Slovnaft VURUP a.s., 2020
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Summary:Firstly, a Python code load massive satellite imagery from a specific folder RGB format, then each raw coral reef image is resized, converted from RGB band to gray, smoothed, and binarized using Open Computer Vision Library available in Python 3.0. The coral reef edge information contains very prominent geometric attributes that characterize their behavior, thus morphological changes were applied to define the contour of the carbonate platform. Furthermore, a structural analysis and shape descriptors were made in a set of images in order to numerically calculate the characteristics of the carbonate platform. A total of 27 satellite images were processed by the algorithm successfully at the same time, only two images were not segmented correctly because of the illumination and intensity of the predominant colors, especially blue color. Finally, this dataset was exported from Microsoft Excel spreadsheets and CSV format respectively.