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Computer vision for automated surface evaluation of concrete bridge decks
Descriptive
TitleInfo
Title
Computer vision for automated surface evaluation of concrete bridge decks
Name
(type = personal)
NamePart
(type = family)
Prasanna
NamePart
(type = given)
Prateek
NamePart
(type = date)
1988-
DisplayForm
PRATEEK PRASANNA
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Dana
NamePart
(type = given)
Kristin J
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Kristin J Dana
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Advisory Committee
Role
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(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Meer
NamePart
(type = given)
Peter
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Peter Meer
Affiliation
Advisory Committee
Role
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internal member
Name
(type = personal)
NamePart
(type = family)
Orfanidis
NamePart
(type = given)
Sophocles
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Sophocles Orfanidis
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2013
DateOther
(qualifier = exact);
(type = degree)
2013-05
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
Structural health monitoring of concrete bridges requires accurate and efficient surface crack detection. Early detection of cracks helps prevent further damage. Safety inspection tests are conducted at regular intervals to assess deterioration. Traditional methods involve detection of cracks by human visual inspection. These methods are costly, inefficient and labor intensive, especially for long-span bridges. This thesis presents the use of computer vision and pattern recognition techniques in assessment of cracks on a concrete bridge surface. Bridge deck images are first collected using high-resolution cameras mounted on a robot. Statistical inference algorithms are then implemented to build an automated crack detection system. The proposed machine learning method reduces manual effort and enables automatic labeling over large bridge deck areas to quantify size and location for future reference or comparisons. A panoramic camera is used for the purpose of context localization. Additionally, we demonstrate image-stitching to obtain a coherent spatial mosaic of the bridge deck.
Subject
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Topic
Electrical and Computer Engineering
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_4670
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
xii, 87 p. : ill.
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Prateek Prasanna
Subject
(authority = ETD-LCSH)
Topic
Structural health monitoring
Subject
(authority = ETD-LCSH)
Topic
Computer vision
Subject
(authority = ETD-LCSH)
Topic
Concrete bridges--Maintenance and repair
Subject
(authority = ETD-LCSH)
Topic
Concrete bridges--Cracking
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917
RelatedItem
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3KK99C9
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
PRASANNA
GivenName
PRATEEK
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2013-04-15 08:04:56
AssociatedEntity
Name
PRATEEK PRASANNA
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ContentModel
ETD
OperatingSystem
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windows xp
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