Vision‐Based Automated Crack Detection for Bridge Inspection. (15th May 2015)

• Record Type: Journal Article
• Authors: Yeum, Chul Min; Dyke, Shirley J.
• Is Part Of: Computer-aided civil and infrastructure engineering. Volume 30:Number 10(2015:Oct.)
• Page Start: 759
• Page End: 770
• Publication Date: 2015-05-15
• Subjects: Civil engineering -- Data processing -- Periodicals; Computer-aided engineering -- Periodicals; 624.0285
• DOI: 10.1111/mice.12141
• Languages: English
• ISSNs: 1093-9687

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Visual inspection of bridges is customarily used to identify and evaluate faults. However, current procedures followed by human inspectors demand long inspection times to examine large and difficult to access bridges. Also, highly relying on an inspector's subjective or empirical knowledge induces false evaluation. To address these limitations, a vision‐based visual inspection technique is proposed by automatically processing and analyzing a large volume of collected images. Images used in this technique are captured without controlling angles and positions of cameras and no need for preliminary calibration. As a pilot study, cracks near bolts on a steel structure are identified from images. Using images from many different angles and prior knowledge of the typical appearance and characteristics of this class of faults, the proposed technique can successfully detect cracks near bolts.</p> </abstract>