Build a classifier to separate images of the four seasons, based on the dominant colors available in images of each season, using the new built-in region operations.
Some public domain images are the source of the seasons' colors.
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The images have different color distributions, but describing them is not easy in the RGB space.
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In the Lab space, the hues are easily separable from the luminance.
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A convex hull is defined from the distribution of the dominant colors for each season with the function ConvexHullMesh.
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Define a distance function from a set of colors to a region using the new RegionDistance function.
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The predicted season is the one that minimizes this distance.