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The Registration and Segmentation of...

Al-Durgham, Mohannad M.

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The Registration and Segmentation of Heterogeneous Laser Scanning Data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Registration and Segmentation of Heterogeneous Laser Scanning Data./
作者:	Al-Durgham, Mohannad M.
面頁冊數:	182 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.
Contained By:	Dissertation Abstracts International76-04B(E).
標題:	Remote Sensing. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3666573
ISBN:	9781321396652

The Registration and Segmentation of Heterogeneous Laser Scanning Data.
Al-Durgham, Mohannad M.

The Registration and Segmentation of Heterogeneous Laser Scanning Data. - 182 p.

Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2014.

This item must not be sold to any third party vendors.

Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data.

ISBN: 9781321396652Subjects--Topical Terms:

1018559
Remote Sensing.

The Registration and Segmentation of Heterogeneous Laser Scanning Data.
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245 1 4 $a The Registration and Segmentation of Heterogeneous Laser Scanning Data.
300 $a 182 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.
500 $a Advisers: Brenda McCabe; Ayman Habib.
502 $a Thesis (Ph.D.)--University of Toronto (Canada), 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data.
520 $a A data characterization and filtering step is proposed to populate the points' attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds.
520 $a Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.
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710 2 $a University of Toronto (Canada). $b Civil Engineering. $3 2104053
773 0 $t Dissertation Abstracts International $g 76-04B(E).
790 $a 0779
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3666573