Multilevel Image Thresholding Using the Complement Feature

Abstract

A novel Eigen formulation is proposed for image segmentation. Each pixel is represented by a unit vector having the x-component as the normalized gray value of the pixel. The axes of inertia are simply the Eigen vectors of the auto-correlation matrix. The largest Eigen vector is used as the point of split. Each sub-image is further split in the same way. The ratio of the smallest Eigen value to the sum of Eigen values represents the percentage of the minority and was used to control further splitting. The process continues until no sub-image is larger in size than this ratio. The results are very encouraging on a wide range of images.