Multi-Material Interface Extraction and its Topological Relationship Expression for 3-D Image Data
Huanhuan Zhang, Lei Wang, Yinghui Wang, Ningna Wang, Xiaojuan Ning, Ke Lv · IEEE Transactions on Instrumentation and Measurement · 2021
The interface extraction and its topological relationship is a critical step toward the visualization, recognition and feature retrieval of multi-material objects. The existing methods only pay attention to the interface visualization and extraction, while ignoring the representation of the interface topological relationship. In this paper, we proposed a multi-material interface extraction and its topological relationship expression method for 3D image data. Firstly, we extend the 2D Canny detector to 3D for extracting the interface-points of 3D image data. Secondly, we introduce an efficient clustering method to cluster interface-points for obtaining the sub-interfaces. Thirdly, the neighboring relationship of each sub-interface is calculated and the directed skeleton tree with global topological feature is constructed. Finally, we propose a matrix representation to explicitly express the topological relationship of interfaces. Experimental results demonstrate that our method can efficiently extract interfaces for a variety of synthetic and raw scanned 3D image data, even in the presence of noisy.