Bayesian marker extraction for color watershed in segmenting microscopic images

In this paper we study the ability of the cooperation of Bayesian color pixel classification in extracting seeds for color watershed. Using color pixel classification alone does not extract accurately enough color regions so we suggest to use a strategy based on three steps: simplification, Bayesian classification and color watershed color watershed is based on an aggregation function using local and global criteria. The strategy is performed on microscopic images. Quantitative measures are used to evaluate the resulting segmentations according to a set of reference images.