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Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale b...

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Autores principales: Mendikute, Alberto, Yagüe-Fabra, José A., Zatarain, Mikel, Bertelsen, Álvaro, Leizea, Ibai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621149/
https://www.ncbi.nlm.nih.gov/pubmed/28891946
http://dx.doi.org/10.3390/s17092066
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author Mendikute, Alberto
Yagüe-Fabra, José A.
Zatarain, Mikel
Bertelsen, Álvaro
Leizea, Ibai
author_facet Mendikute, Alberto
Yagüe-Fabra, José A.
Zatarain, Mikel
Bertelsen, Álvaro
Leizea, Ibai
author_sort Mendikute, Alberto
collection PubMed
description Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g., 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras.
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spelling pubmed-56211492017-10-03 Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining Mendikute, Alberto Yagüe-Fabra, José A. Zatarain, Mikel Bertelsen, Álvaro Leizea, Ibai Sensors (Basel) Article Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g., 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras. MDPI 2017-09-09 /pmc/articles/PMC5621149/ /pubmed/28891946 http://dx.doi.org/10.3390/s17092066 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mendikute, Alberto
Yagüe-Fabra, José A.
Zatarain, Mikel
Bertelsen, Álvaro
Leizea, Ibai
Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title_full Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title_fullStr Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title_full_unstemmed Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title_short Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining
title_sort self-calibrated in-process photogrammetry for large raw part measurement and alignment before machining
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621149/
https://www.ncbi.nlm.nih.gov/pubmed/28891946
http://dx.doi.org/10.3390/s17092066
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