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1 February 1992 Three-dimensional image segmentation and recognition in an intelligent vision system
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dongping Zhu, Richard W. Conners, and Philip A. Araman "Three-dimensional image segmentation and recognition in an intelligent vision system", Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); https://doi.org/10.1117/12.57076
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