Rule-based system to reconstruct 3-D tree structure from two views

Iching Liu; Ying Sun

doi:10.1117/12.50315

1 November 1991 Rule-based system to reconstruct 3-D tree structure from two views

Iching Liu, Ying Sun

Proceedings Volume 1606, Visual Communications and Image Processing '91: Image Processing; (1991) https://doi.org/10.1117/12.50315
Event: Visual Communications, '91, 1991, Boston, MA, United States

Abstract

We propose a fully automatic system that reconstructs a 3-D tree structure based on two images taken from mutually orthogonal directions. The system comprises two major components, the high-level knowledge base and the low-level signal processing algorithms. Computational algorithms are responsible for tracking segments in each image, representing 2- D segments with directed graphs, and reconstructing 3-D segments from matching 2-D segment pairs. Knowledge of epipolar constraint, segments geometry, and connectivity are used to resolve the problem of matching segments between two views. Interaction between segmentation and matching is facilitated by uncertain reasoning. The knowledge base is represented by production rules which are implemented in the CLIPS shell. The computational algorithms are coded in the C language. The performance of the system is evaluated with images of a tree-like model. The total processing time for reconstruction of this tree-like model with 256³ resolution is 14 seconds on a workstation. The results show that the system is capable of correctly delineating an object's 3-D tree structure. This study demonstrates a non model-based approach to two-view reconstruction of tree-like structures.

Citation Download Citation

Iching Liu and Ying Sun "Rule-based system to reconstruct 3-D tree structure from two views", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50315

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KEYWORDS

Image segmentation

3D image processing

Image processing

3D modeling

Angiography

Reconstruction algorithms

Detection and tracking algorithms

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