Random Walker Image Segmentation Algorithm

This article presents the MATLAB source code implementation for Random Walker image segmentation. The code requires installation of the Graph Analysis Toolbox, which can be downloaded from http://eslab.bu.edu/software/graphanalysis/. This toolbox provides essential graph theory functions that are crucial for image analysis tasks, enabling better understanding and processing of image structures through graph representation. The Random Walker algorithm operates by modeling an image as a graph where pixels represent nodes connected by edges weighted according to intensity similarities. The implementation utilizes MATLAB's sparse matrix capabilities for efficient graph operations and solves the combinatorial Dirichlet problem to determine segmentation boundaries. Key functions include graph construction, Laplacian matrix computation, and solving linear systems for probability diffusion. We have included a practical application example that demonstrates how to initialize seed points, compute probabilities for unlabeled pixels reaching each seed, and assign final labels based on maximum probabilities. This example helps users understand the practical implementation of the algorithm and its parameter tuning. Should you have any questions regarding the code implementation, algorithm details, or toolbox usage, please feel free to contact us for technical support.