MATLAB Code Implementation of the Normalized Cut (Ncut) Segmentation Algorithm

In this article, I present the MATLAB implementation of the Normalized Cut (Ncut) segmentation algorithm. The implementation includes several MATLAB code segments that demonstrate key aspects of the algorithm, along with a supporting image for visualization. The code covers essential components such as affinity matrix construction using Gaussian similarity measures, eigenvalue decomposition for solving generalized eigenvalue problems, and recursive bipartitioning for multi-region segmentation. Key functions implemented include weight matrix calculation, spectral clustering operations, and segmentation visualization routines. These resources provide valuable insights into graph-based image segmentation techniques, making them suitable for both beginners and experienced programmers seeking to understand or modify the algorithm for specific applications. The accompanying image illustrates the segmentation results, helping users validate their implementation. Should you have any questions or require further assistance with the code adaptation, please feel free to contact me. Enjoy your learning journey!