Surface scanning with uncoded structured light sources.

ROBINSON, Alan. (2005). Surface scanning with uncoded structured light sources. Doctoral, Sheffield Hallam University (United Kingdom)..

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Abstract

Structured Light Scanners measure the surface of a target object, producing a set of vertices which can be used to construct a three-dimensional model of the surface. The techniques are particularly appropriate for measuring the smoothly undulating, featureless forms which Stereo Vision methods find difficult, and the structured light pattern explicitly gives a dense graph of connected vertices, thus obviating the need for vertex-triangulation prior to surface reconstruction. In addition, the technique provides the measurements almost instantaneously, and so is suitable for scanning moving and non-rigid objects. Because of these advantages there is an imperative to extend the range of scannable surfaces to those including occlusions, which often reduce or prevent successful measurement.This thesis investigates ways of improving both the accuracy and the range of surface types which can be scanned using structured light techniques, extending current research by examining the role of occlusions and geometric constraints, and introducing novel algorithms to solve the Indexing Problem. The Indexing Problem demands that for every pattern element in the projected image, its counterpart, reflected from the surface of the target object, must be found in the recorded image, and most researchers have declared this problem to be intractable without resorting to coding schemes which uniquely identify each pattern element. The use of uncoded projection patterns, where the pattern elements are projected without any unique identification, has two advantages: firstly it provides the densest possible set of measured vertices within a single video timeframe, and secondly it allows the investigation of the fundamental problems without the distraction of dealing with coding schemes. These advantages educe the general strategy adopted in this thesis, of attempting to solve the Indexing Problem using uncoded patterns, and then adding some coding where difficulties still remain.In order to carry out these investigations it is necessary to precisely measure the system and its outputs, and to achieve this requirement two scanners have been built, a Single Stripe Scanner and a Multiple Stripe Scanner. The Single Stripe Scanner introduces the geometric measurement methods and provides a reference output which matches the industry standard; the Multiple Stripe Scanner then tests the results of the investigations and evaluates the success of the new algorithms and constraints. In addition, some of the investigations are tested theoretically, by using synthetic data and by the solution of geometric diagrams.These evaluations of success show that, if occlusions are not present in the recorded data, the Indexing Problem can often be completely solved if the new indexing algorithms and geometric constraints are included. Furthermore, while there are some cases where the Indexing Problem cannot be solved without recourse to a coding scheme, the addition of occlusion detection in the algorithms greatly improves the indexing accuracy and therefore the successful measurement of the target surface.

Item Type: Thesis (Doctoral)
Additional Information: Thesis (Ph.D.)--Sheffield Hallam University (United Kingdom), 2005.
Research Institute, Centre or Group: Sheffield Hallam Doctoral Theses
Depositing User: EPrints Services
Date Deposited: 10 Apr 2018 17:21
Last Modified: 10 Apr 2018 17:21
URI: http://shura.shu.ac.uk/id/eprint/20284

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