3-dimensional surface imaging using Active Wavefront Sampling

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006. === Includes bibliographical references (p. 129-130). === A novel 3D surface imaging technique using Active Wavefront Sampling (AWS) is presented. In this technique, the optical wavefront traversing a lens...

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Main Author: Frigerio, Federico, Ph. D. Massachusetts Institute of Technology
Other Authors: Douglas P. Hart.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2007
Subjects:
Online Access:http://hdl.handle.net/1721.1/38258
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-382582019-05-02T16:34:58Z 3-dimensional surface imaging using Active Wavefront Sampling Three-dimensional surface imaging using AWS Frigerio, Federico, Ph. D. Massachusetts Institute of Technology Douglas P. Hart. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006. Includes bibliographical references (p. 129-130). A novel 3D surface imaging technique using Active Wavefront Sampling (AWS) is presented. In this technique, the optical wavefront traversing a lens is sampled at two or more off-axis locations and the resulting motion of each target feature is measured. This target feature image motion can be used to calculate the feature's distance to the camera. One advantage of this approach over traditional stereo techniques is that only one optical train and one sensor can be used to obtain depth information, thereby reducing the bulk and the potential cost of the equipment. AWS based systems are also flexible operationally in that the number of sampling positions can be increased or decreased to respectively raise the accuracy or to raise the processing speed of the system. Potential applications include general machine vision tasks, 3D endoscopy, and microscopy. The fundamental depth sensitivity of an AWS based system will be discussed, and practical implementations of the approach will be described. Algorithms developed to track target features in the images captured at different aperture sampling positions will be discussed, and a method for calibrating an AWS based method will also be described. by Federico Frigerio. Ph.D. 2007-08-03T18:21:55Z 2007-08-03T18:21:55Z 2006 2006 Thesis http://hdl.handle.net/1721.1/38258 150961779 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 130 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Mechanical Engineering.
spellingShingle Mechanical Engineering.
Frigerio, Federico, Ph. D. Massachusetts Institute of Technology
3-dimensional surface imaging using Active Wavefront Sampling
description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006. === Includes bibliographical references (p. 129-130). === A novel 3D surface imaging technique using Active Wavefront Sampling (AWS) is presented. In this technique, the optical wavefront traversing a lens is sampled at two or more off-axis locations and the resulting motion of each target feature is measured. This target feature image motion can be used to calculate the feature's distance to the camera. One advantage of this approach over traditional stereo techniques is that only one optical train and one sensor can be used to obtain depth information, thereby reducing the bulk and the potential cost of the equipment. AWS based systems are also flexible operationally in that the number of sampling positions can be increased or decreased to respectively raise the accuracy or to raise the processing speed of the system. Potential applications include general machine vision tasks, 3D endoscopy, and microscopy. The fundamental depth sensitivity of an AWS based system will be discussed, and practical implementations of the approach will be described. Algorithms developed to track target features in the images captured at different aperture sampling positions will be discussed, and a method for calibrating an AWS based method will also be described. === by Federico Frigerio. === Ph.D.
author2 Douglas P. Hart.
author_facet Douglas P. Hart.
Frigerio, Federico, Ph. D. Massachusetts Institute of Technology
author Frigerio, Federico, Ph. D. Massachusetts Institute of Technology
author_sort Frigerio, Federico, Ph. D. Massachusetts Institute of Technology
title 3-dimensional surface imaging using Active Wavefront Sampling
title_short 3-dimensional surface imaging using Active Wavefront Sampling
title_full 3-dimensional surface imaging using Active Wavefront Sampling
title_fullStr 3-dimensional surface imaging using Active Wavefront Sampling
title_full_unstemmed 3-dimensional surface imaging using Active Wavefront Sampling
title_sort 3-dimensional surface imaging using active wavefront sampling
publisher Massachusetts Institute of Technology
publishDate 2007
url http://hdl.handle.net/1721.1/38258
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