TY - JOUR
T1 - Adapting 360-degree cameras for culvert inspection
T2 - Case study
AU - Meegoda, Jay N.
AU - Kewalramani, Jitendra A.
AU - Saravanan, Akila
N1 - Publisher Copyright:
© 2018 American Society of Civil Engineers.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Prior video technologies such as closed-circuit television (CCTV) cameras have been used for culvert inspection. They are limited by the range of the area scanned and by the direction in which the camera is oriented because of a limited field of view (FOV). In this research, a 360-degree camera mounted on a remote-controlled crawler was designed and modified to travel through a culvert to scan and take videos of the culvert's interiors. With the unique mounting and coverage of the 360-degree camera, a continuous view of the inner walls of the culvert was captured, as if by a human eye, making visual inspection of hard-to-reach areas possible. The video was analyzed manually, and areas suggesting defects were studied. Snapshots of defective areas were further analyzed using computer software developed in-house, where defects were identified by differences in color and texture. Calculations made from the data collected helped to pinpoint the location of the defects within the culvert and estimate the area of the defects in order to provide culvert inspectors with quantitative information on the condition of the infrastructure.
AB - Prior video technologies such as closed-circuit television (CCTV) cameras have been used for culvert inspection. They are limited by the range of the area scanned and by the direction in which the camera is oriented because of a limited field of view (FOV). In this research, a 360-degree camera mounted on a remote-controlled crawler was designed and modified to travel through a culvert to scan and take videos of the culvert's interiors. With the unique mounting and coverage of the 360-degree camera, a continuous view of the inner walls of the culvert was captured, as if by a human eye, making visual inspection of hard-to-reach areas possible. The video was analyzed manually, and areas suggesting defects were studied. Snapshots of defective areas were further analyzed using computer software developed in-house, where defects were identified by differences in color and texture. Calculations made from the data collected helped to pinpoint the location of the defects within the culvert and estimate the area of the defects in order to provide culvert inspectors with quantitative information on the condition of the infrastructure.
KW - 360-degree camera
KW - Culvert inspection
KW - Defect size
KW - Video analysis
UR - http://www.scopus.com/inward/record.url?scp=85054089464&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054089464&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)PS.1949-1204.0000352
DO - 10.1061/(ASCE)PS.1949-1204.0000352
M3 - Article
AN - SCOPUS:85054089464
SN - 1949-1190
VL - 10
JO - Journal of Pipeline Systems Engineering and Practice
JF - Journal of Pipeline Systems Engineering and Practice
IS - 1
M1 - 05018005
ER -