Computer vision based crack detection and analysis

Prateek Prasanna, Kristin Dana, Nenad Gucunski, Basily Basily

Research output: Chapter in Book/Report/Conference proceedingConference contribution

38 Scopus citations

Abstract

Cracks on a bridge deck should be ideally detected at an early stage in order to prevent further damage. To ensure safety, it is necessary to inspect the quality of concrete decks at regular intervals. Conventional methods usually include manual inspection of concrete surfaces to determine defects. Though very effective, these methods are time-inefficient. This paper presents the use of computer-vision techniques in detection and analysis of cracks on a bridge deck. High quality images of concrete surfaces are captured and subsequently analyzed to build an automated crack classification system. After feature extraction using the training set images, statistical inference algorithms are employed to identify cracks. The results demonstrate the feasibility of the proposed crack observation and classification system.

Original languageEnglish (US)
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012
DOIs
StatePublished - May 22 2012
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012 - San Diego, CA, United States
Duration: Mar 12 2012Mar 15 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8345
ISSN (Print)0277-786X

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012
CountryUnited States
CitySan Diego, CA
Period3/12/123/15/12

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Classification
  • Computer vision
  • Cracks

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