Open Access
31 January 2017 Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration
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Abstract
Rapid development in the performance of sophisticated optical components, digital image sensors, and computer abilities along with decreasing costs has enabled three-dimensional (3-D) optical measurement to replace more traditional methods in manufacturing and quality control. The advantages of 3-D optical measurement, such as noncontact, high accuracy, rapid operation, and the ability for automation, are extremely valuable for inline manufacturing. However, most of the current optical approaches are eligible for exterior instead of internal surfaces of machined parts. A 3-D optical measurement approach is proposed based on machine vision for the 3-D profile measurement of tiny complex internal surfaces, such as internally threaded holes. To capture the full topographic extent (peak to valley) of threads, a side-view commercial rigid scope is used to collect images at known camera positions and orientations. A 3-D point cloud is generated with multiview stereo vision using linear motion of the test piece, which is repeated by a rotation to form additional point clouds. Registration of these point clouds into a complete reconstruction uses a proposed automated feature-based 3-D registration algorithm. The resulting 3-D reconstruction is compared with x-ray computed tomography to validate the feasibility of our proposed method for future robotically driven industrial 3-D inspection.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Yuanzheng Gong and Eric J. Seibel "Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration," Optical Engineering 56(1), 014108 (31 January 2017). https://doi.org/10.1117/1.OE.56.1.014108
Received: 18 August 2016; Accepted: 10 January 2017; Published: 31 January 2017
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CITATIONS
Cited by 23 scholarly publications and 1 patent.
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KEYWORDS
Cameras

3D metrology

3D image processing

Clouds

Image registration

X-rays

3D modeling

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