Extracting curbside storm drain locations from street-level images
Depwe, Elizabeth E.
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https://hdl.handle.net/2142/88213
Description
Title
Extracting curbside storm drain locations from street-level images
Author(s)
Depwe, Elizabeth E.
Issue Date
2015-07-17
Director of Research (if dissertation) or Advisor (if thesis)
Peschel, Joshua
Committee Member(s)
Rutherford, Cassandra
Department of Study
Civil & Environmental Engineering
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
infrastructure assessment
computer vision
Google Street View
data mining
stormwater management
image detection
image processing
Abstract
This thesis presents a machine vision procedure to identify and extract storm drain locations from natural images along surface street curbsides. Existing storm drain infrastructure information is commonly reposed by managing agencies in either paper or digital format. Access to these data for urban hydrologic and hydraulic modeling purposes may be limited by security protocols and/or the format in which the data may be available. The procedure described in this work uses a novel vision algorithm with Google Street View imagery to identify and extract the locations of curbside storm drains. Results are converted into a tabular format that can be converted into geometric input files for modeling purposes. This fast, approximation approach to assembling storm drain data could be of interest to public works managers, urban hydrology and hydraulics practitioners and researchers, and citizen scientists, to improve general understanding of the civil and environmental infrastructure.
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