CT image sequence analysis for object recognition-a rule based 3-D computer vision system

Author

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

Author_Institution

Spatial Data Anal. Lab., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

fYear

1991

fDate

13-16 Oct 1991

Firstpage

173

Abstract

The authors present a rule-based, three-dimensional (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. The use of different knowledge sources in a set of independent and concise rules is illustrated

Keywords

automatic optical inspection; computational geometry; computer vision; computerised pattern recognition; knowledge based systems; statistical analysis; topology; 3-D computer vision; CT image sequence analysis; computerised pattern recognition; computerised tomography; confidence values; evidence functions; geometric attribute; inspection; knowledge sources; rule based systems; statistical attributes; topological attribute; wood defect identification; Attenuation; Computed tomography; Computer industry; Computer vision; Image recognition; Image segmentation; Image sequence analysis; Labeling; Machine vision; X-ray imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on

Conference_Location

Charlottesville, VA

Print_ISBN

0-7803-0233-8

Type

conf

DOI

10.1109/ICSMC.1991.169680

Filename

169680