Parallel genetic algorithm based adaptive thresholding for image segmentation under uneven lighting conditions

In this paper, two adaptive thresholding schemes have been proposed. These two schemes are based on adaptive selection of windows based on the proposed window merging and window growing. Windows are selected based on the entropy and feature entropy criterion. PGA and MMSE based segmentation schemes have been proposed to segment the windows selected a priori. The efficacy of the proposed approaches have been compared with the Huang´s pyramidal window merging approach. It is found that the proposed approaches exhibited improved performance in the context of accuracy of segmentation.