Recognition of Blends Based on Spring Edge Groups and Attribute Adjacency Graph
Song Nian Yu, Zhao Yingfeng, Jiangtao Ma · 2024
This paper presents a novel blend recognition algorithm that identifies various blends in 3D models. The proposed approach combines the Spring Edge Groups (SEGs) and Attribute Adjacency Graph (AAG) methods to improve the accuracy and efficiency of blend recognition. The key algorithm includes a SEG-based recognition algorithm and adapts recognition steps based on these SEGs. Additionally, the AAG is employed to accurately detect Corner-blend faces (CBFs). The algorithm's performance was validated through extensive experimentation using models with diverse blend features, demonstrating its effectiveness in handling these features.