Currently I am generating an ID from an image by using K-Means to seperate brightness levels into 8 levels (clusters) and order them brightest to darkest. For each cluster I calculate: 1) Their center points as a percentage of image size (using average pixel coordinates) 2) Average distance of points from the center as a percentage of image size 3) Angle between horizontal axis and the line along which the distribution is the highest 4) Percentage of total area occupied ID example (a total of 8 entries in each list (entry per cluster)): Centers = [24%, 77%], [56%, 29%], [58%, 87%], ... Average distance of point from center of cluster = 12%, 17%, 9%, 30%,... Angle between horizontal axis and the highest distribution line (0 to 180 i.e. non-directional) = 55, 10, 155,... Area occupied = 7%, 16%, 10%,... For my purposes it should not be possible to generate an image with the same ID by using the original image ID. But would it be possible to do that? I'm only asking about feasibility of creating an image to fit that criteria, not necessarily how you'd do it. Please ask if anything is unclear - I do feel like the question can be confusing. Thanks for your time, Povilas P.S. Sorry if I posted in the wrong sub-forum, I was not sure where I should ask this.