K-Means-Color-Clustering | nifty little demonstration of using k

K-Means-Color-Clustering is a Java library. K-Means-Color-Clustering has no bugs, it has no vulnerabilities and it has low support. However K-Means-Color-Clustering build file is not available. You can download it from GitHub.

################## what is k-means? #################. k-means is an algorithm that is used in many different problem domains. it works by creating centroids, or clusters, that hold specific values - whether rgb color values or an arbitrary size threshold - and then assigning data points to clusters based some distance measurement. for instance, in this program, the user selects four clusters by clicking on points in the window. the rgb and xy values of the selected point become the cluster values. then, by iterating through every pixel in the image, we can check which pixels belong to which cluters using a euclidean distance metric. this process is run until all pixels have been normalized into a cluster, resulting in a posterizing type effect. although this a rudimentary application of k-means, it can still be used to develop powerful and interesting programs. my next project is focused on using k-means to transform photographs into sprite images reminscient of vintage video games. in that case, the centroids will be composed of the color values for specific templates (commodore 64, atari 2600, nes, etc). ####################### how to use this program #######################.