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To identify a colour that best represents an image, we need to understand that colour can be numerically represented in many , many ways (https://en.wikipedia.org/wiki/Color_model ), called colour models. When an image, stored as a jpg or png or other file format, is loaded into a computer, the colour of each pixel can be numerically represented by passing saved information to any of these colour models.
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Taking the depth registered row image (see Preprocessing Analytics Ready Data (Image Preparation + Depth Registration) for more information).
Extract every pixel from the image, and plot each RGB triplet onto a 3 axis plot.
Cluster all the RGB values into five clusters.
Determine the cluster with the highest number of pixels. This is the dominant cluster.
Find the geometric centre of the dominant cluster. The R, G and B values of this point is our Dominant Colour.
Convert the RGB value to hex and export both .
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File Header | Description |
hole_id | Customer’s Hole ID |
depth_from_m | Start of interval (metres) |
depth_to_m | End of interval (metres) |
R | Red component of the dominant colour |
G | Green component of the dominant colour |
B | Blue component of the dominant colour |
hex | Hex colour code for the dominant colour |
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Version | Date | Author | Rationale |
1 | 6 Dec 2023 | S Johnson | Initial release |
2 | 29 Jan 2023 | S Johnson | Updated units for outputs |