Persistence-Based Skeletonization of Images

Explore persistence-based techniques for image skeletonization in this 30-minute lecture by Vitaliy Kurlin. Delve into the challenge of dividing images into convex polygons with subpixel precision vertices, allowing edges to follow any direction while adhering to object boundaries. Examine recent algorithms grounded in topological persistence, including the Convex Constrained Mesh (CCM) and the Persistent Resolution-Independent Mesh (PRIM). Learn how CCM processes straight line segments to produce a complete mesh of convex polygons, avoiding small angles and offering approximation guarantees. Discover how PRIM automatically detects straight-line edges based on contrast strength differences. Gain insights into advanced image processing techniques that combine algebraic topology and computer vision.

Vitaliy Kurlin (6/2/20): Persistence-based skeletonization of images