مشخصات پژوهش

Image segmentation—the process of partitioning an image into multiple meaningful regions—is a foundational task in computer vision, medical imaging, remote sensing, and numerous other scientific and industrial applications. Among the many approaches developed for this purpose, variational methods based on partial differential equations (PDEs) have proven particularly powerful. The Chan–Vese (CV) model, a landmark piecewise-constant active contour method, revolutionized region-based segmentation by minimizing an energy functional that balances region homogeneity and contour smoothness. However, the original CV model is limited to binary (two-phase) segmentation and can suffer from computational inefficiencies when extended to multiphase problems.