Circular histogram thresholding is a method to separate objects from backgrounds in color images. Maximum entropy thresholding on circular histograms is a technique that finds the best thresholds for this task, but it is slow. A new recursive algorithm has been developed to speed up this process, making it more efficient than previous methods. This algorithm can also be extended to work with multiple classes, improving the segmentation of images even further.