Two-Dimensional Otsu Automatic Thresholding Method for Grayscale Images

The two-dimensional Otsu automatic thresholding method for grayscale images represents a fundamental approach in image processing applications. This technique operates by computing a two-dimensional histogram of the input image, followed by determining an optimal threshold value that effectively partitions the image into two distinct regions. The provided MATLAB implementation enables complete automation of this 2D Otsu segmentation process while incorporating precise execution time measurement. The algorithm implementation includes key functions for calculating joint probability distributions and maximizing between-class variance criteria to establish the optimal threshold. This program facilitates convenient grayscale image segmentation, allowing users to efficiently extract regions of interest through automated threshold determination. The code structure supports straightforward integration with existing image processing pipelines and provides visualization capabilities for analyzing the resulting 2D histogram distributions.