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Proceedings Paper

Three-dimensional image segmentation and recognition in an intelligent vision system
Author(s): Dongping Zhu; Richard W. Conners; Philip A. Araman
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Paper Abstract

Research is underway to apply computerized tomography (CT) imaging to hardwood log inspection in the forest products industry. For this purpose, an intelligent vision system is being created that is aimed at locating, identifying, and quantifying the internal defects inside logs by analyzing their CT image data. This inspection system is designed to be wood species independent. It is composed of three components: a CT scanner-based data acquisition system; a low-level module for image segmentation; and a high-level module for defect recognition. Defect quantification is attained by computing the volume and orientation of each defect. This paper discusses the problems of segmenting CT image sequence and 3-D object detection by a rule-based expert system approach. Experimental results with real-world images of different hardwood log species are provided to show the usefulness, efficacy, and robustness of the proposed inspection system. This allows solutions to hardwood log inspection, as well as to problems in other nondestructive testing applications where image analysis plays an important role.

Paper Details

Date Published: 1 February 1992
PDF: 12 pages
Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); doi: 10.1117/12.57076
Show Author Affiliations
Dongping Zhu, Virginia Polytechnic Institute and State Univ. (United States)
Richard W. Conners, Virginia Polytechnic Institute and State Univ. (United States)
Philip A. Araman, USDA Forest Service Southeastern Experiment Station (United States)

Published in SPIE Proceedings Vol. 1607:
Intelligent Robots and Computer Vision X: Algorithms and Techniques
David P. Casasent, Editor(s)

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