CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System

Dongping Zhu; Richard W. Conners; Daniel L. Schmoldt; Philip Araman

doi:10.1109/icsmc.1991.169680

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CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System

Informally Refereed

Authors:

Dongping Zhu, Richard W. Conners, Daniel L. Schmoldt, Philip Araman

Year:

1991

Type:

Scientific Journal

Station:

Southern Research Station

DOI:

https://doi.org/10.1109/icsmc.1991.169680

Source:

Proceedings, 1991 IEEE International Conference on Systems, Man, and Cybernetics. pp. 173-178.

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Abstract

Research is now underway to create a vision system for hardwood log inspection using a knowledge-based approach. In this paper, we present a rule-based, 3-D vision system for locating and identifying wood defects using topological, geometric, and statistical attributes. A number of different features can be derived from the 3-D input scenes. These features and evidence functions are used to compute confidence values for object membership in different defect classes. We will illustrate the use of different knowledge sources in a set of independent and concise rules.

Citation

Zhu, Dongping; Conners, Richard W.; Schmoldt, Daniel L.; Araman, Philip A. 1991. CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System. Proceedings, 1991 IEEE International Conference on Systems, Man, and Cybernetics. pp. 173-178.