How to construct polygons from a 2D data to compute spatial autocorrelation in R

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I am new to the concept of spatial autocorrelation. I have a dataset of the form (x-coordinate, y-coordinate, value), a plot of which looks like this image. I wish to perform a spatial autocorrelation test using the Global Moran's I. Therefore I need to define my polygons and specify neighbors. I want each individual contiguous color cluster in the image to form a polygon. My question is, how can achieve this in R? Are there any libraries that can read the image data and set the latitude and longitude values for use? Any suggestions will help. thanks

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