Global thresholding algorithm based on boundary selection

A global image thresholding algorithm based on boundary selection is proposed for improving conventional histogram-based thresholding algorithms. An image is divided into blocks of a fixed size, and the pixel variance of each block is used for finding the boundary blocks that a bimodal histogram. Otsu's threshold value of boundary block is used to classify object blocks and background blocks. The average values of these blocks are used to determine the optimal threshold value. Experimental results show that proposed algorithm improves on conventional thresholding methods for various types of images.