Image segmentation based on gray-level spatial correlation maximum between-cluster variance

Abstract

When processing the background and target blurred image, 1D-Otsu and 2D-Otsu segmentation effect is not good. The proposed algorithm used the gray value of the pixels and their similarity with neighboring pixels in gray value to build a histogram which was called gray-level spatial correlation histogram. Then threshold value is obtained by calculating GLSC histogram maximum between-class variance. Integral figure was introduced in order to make the time complexity from original 2 2