Paper
6 April 2012 Computer-vision based crack detection and analysis
Prateek Prasanna, Kristin Dana, Nenad Gucunski, Basily Basily
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Prateek Prasanna, Kristin Dana, Nenad Gucunski, and Basily Basily "Computer-vision based crack detection and analysis", Proc. SPIE 8345, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012, 834542 (6 April 2012); https://doi.org/10.1117/12.915384
Lens.org Logo
CITATIONS
Cited by 39 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Bridges

Statistical analysis

Inspection

Classification systems

Detection and tracking algorithms

Edge detection

Nondestructive evaluation

Back to Top