Recognition of closed pockets based on adjacency graph decomposition

Closed pockets are common features in milling process, but generalized recognition methods remain scarce. This work analyzes closed pocket characterization using adjacency graphs derived from 3D models. We propose an innovative generalized recognition method employing an adjacency graph decomposition algorithm. Results show that, unlike subgraph retrieval or deep learning, this approach effectively recognizes complex pockets’ closed pockets without relying on their internal structure. Adaptable across diverse part types, the method offers broad industrial application potential.