Generation of brightness membership functions for labeled image segmentation

A common problem in segmentation of monochrome images occurs when an image has a background of varying gray level such as gradually changing shades, or when collections we would like to call regions, or classes, assume some broad range of gray scales. These problems hinder the use of brightness feature within segmentation algorithms of monochrome images. We propose a method for deriving membership functions for the labels related to the brightness feature, to be included within fuzzy labeled segmentation algorithms. With the aim to be useful for a wide range of detection and segmentation applications, the method is based on the use of a rule base analysis of the brightness histogram, heuristics, and probability to possibility transformations. We illustrate the suitability and applicability of our membership functions generation method with applications to real data sets.