Pavement crack mosaicking based on crack detection quality

Y. Yoon, S. Bang, F. Baek, H. Kim

Research output: Contribution to conferencePaper

Abstract

A vehicle-mounted video camera, which is one of low-cost off-the-shelf devices, can be used economically for pavement crack monitoring. The pavement frames obtained by the video camera can be merged to form a mosaic image, from which road distress information can be extracted. However, quality of crack detection in the frames is different from one another. The different level of crack detection quality should be considered for accurate construction of crack mosaic. This paper proposes a new pavement crack mosaicking method based on quality of crack detection in each frame. A convolutional neural network is suggested as a way to evaluate the quality of crack detection in the video frames. The proposed method showed a promising mosaicking performance compared to other existing methods.

Original languageEnglish
Pages1197-1201
Number of pages5
Publication statusPublished - 2019 Jan 1
Event36th International Symposium on Automation and Robotics in Construction, ISARC 2019 - Banff, Canada
Duration: 2019 May 212019 May 24

Conference

Conference36th International Symposium on Automation and Robotics in Construction, ISARC 2019
CountryCanada
CityBanff
Period19/5/2119/5/24

Fingerprint

Crack detection
Pavements
Cracks
Video cameras
Neural networks
Monitoring
Costs

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Building and Construction
  • Human-Computer Interaction

Cite this

Yoon, Y., Bang, S., Baek, F., & Kim, H. (2019). Pavement crack mosaicking based on crack detection quality. 1197-1201. Paper presented at 36th International Symposium on Automation and Robotics in Construction, ISARC 2019, Banff, Canada.
Yoon, Y. ; Bang, S. ; Baek, F. ; Kim, H. / Pavement crack mosaicking based on crack detection quality. Paper presented at 36th International Symposium on Automation and Robotics in Construction, ISARC 2019, Banff, Canada.5 p.
@conference{78611da9ae4e4b8e90710847bd4064db,
title = "Pavement crack mosaicking based on crack detection quality",
abstract = "A vehicle-mounted video camera, which is one of low-cost off-the-shelf devices, can be used economically for pavement crack monitoring. The pavement frames obtained by the video camera can be merged to form a mosaic image, from which road distress information can be extracted. However, quality of crack detection in the frames is different from one another. The different level of crack detection quality should be considered for accurate construction of crack mosaic. This paper proposes a new pavement crack mosaicking method based on quality of crack detection in each frame. A convolutional neural network is suggested as a way to evaluate the quality of crack detection in the video frames. The proposed method showed a promising mosaicking performance compared to other existing methods.",
author = "Y. Yoon and S. Bang and F. Baek and H. Kim",
year = "2019",
month = "1",
day = "1",
language = "English",
pages = "1197--1201",
note = "36th International Symposium on Automation and Robotics in Construction, ISARC 2019 ; Conference date: 21-05-2019 Through 24-05-2019",

}

Yoon, Y, Bang, S, Baek, F & Kim, H 2019, 'Pavement crack mosaicking based on crack detection quality' Paper presented at 36th International Symposium on Automation and Robotics in Construction, ISARC 2019, Banff, Canada, 19/5/21 - 19/5/24, pp. 1197-1201.

Pavement crack mosaicking based on crack detection quality. / Yoon, Y.; Bang, S.; Baek, F.; Kim, H.

2019. 1197-1201 Paper presented at 36th International Symposium on Automation and Robotics in Construction, ISARC 2019, Banff, Canada.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Pavement crack mosaicking based on crack detection quality

AU - Yoon, Y.

AU - Bang, S.

AU - Baek, F.

AU - Kim, H.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - A vehicle-mounted video camera, which is one of low-cost off-the-shelf devices, can be used economically for pavement crack monitoring. The pavement frames obtained by the video camera can be merged to form a mosaic image, from which road distress information can be extracted. However, quality of crack detection in the frames is different from one another. The different level of crack detection quality should be considered for accurate construction of crack mosaic. This paper proposes a new pavement crack mosaicking method based on quality of crack detection in each frame. A convolutional neural network is suggested as a way to evaluate the quality of crack detection in the video frames. The proposed method showed a promising mosaicking performance compared to other existing methods.

AB - A vehicle-mounted video camera, which is one of low-cost off-the-shelf devices, can be used economically for pavement crack monitoring. The pavement frames obtained by the video camera can be merged to form a mosaic image, from which road distress information can be extracted. However, quality of crack detection in the frames is different from one another. The different level of crack detection quality should be considered for accurate construction of crack mosaic. This paper proposes a new pavement crack mosaicking method based on quality of crack detection in each frame. A convolutional neural network is suggested as a way to evaluate the quality of crack detection in the video frames. The proposed method showed a promising mosaicking performance compared to other existing methods.

UR - http://www.scopus.com/inward/record.url?scp=85071486374&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071486374&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85071486374

SP - 1197

EP - 1201

ER -

Yoon Y, Bang S, Baek F, Kim H. Pavement crack mosaicking based on crack detection quality. 2019. Paper presented at 36th International Symposium on Automation and Robotics in Construction, ISARC 2019, Banff, Canada.