Image-based retro-reflectivity measurement of traffic signs in day time. Issue 4 (October 2015)
- Record Type:
- Journal Article
- Title:
- Image-based retro-reflectivity measurement of traffic signs in day time. Issue 4 (October 2015)
- Main Title:
- Image-based retro-reflectivity measurement of traffic signs in day time
- Authors:
- Balali, Vahid
Sadeghi, Mohammad Amin
Golparvar-Fard, Mani - Abstract:
- Graphical abstract: Highlights: A vision method that remotely measures traffic sign retro-reflectivity in daytime. The method simulates nighttime visibility from images taken during daytime. The impact of time of day and distance on measurements are studied. The method with accuracy of 95.24% is cheaper, faster and safer than current practice. The method satisfies FHWA measurement requirements on accuracy and granularity. Abstract: The visibility of a traffic sign at night depends on its retro-reflectivity, a property that needs to be frequently monitored to ensure transportation safety. In the U.S., Federal Highway Administration (FHWA) maintains regulations to ensure minimum retro-reflectivity levels. Current measurement techniques either (a) use vehicle mounted device during the night, or (b) use manual handheld devices during the day. The former is expensive due to nighttime labor cost. The latter is time-consuming and unsafe. To address these limitations, this paper presents a computer vision-based technique to measure retro-reflectivity during daytime using a vehicle mounted device. The presented algorithms simulate nighttime visibility of traffic signs from images taken during daytime and measure their retro-reflectivity. The technique is faster, cheaper, and safer as it neither requires nighttime operation nor requires manual sign inspection. It also satisfies FHWA measurement guidelines both in terms of granularity and accuracy. The performance of the presentedGraphical abstract: Highlights: A vision method that remotely measures traffic sign retro-reflectivity in daytime. The method simulates nighttime visibility from images taken during daytime. The impact of time of day and distance on measurements are studied. The method with accuracy of 95.24% is cheaper, faster and safer than current practice. The method satisfies FHWA measurement requirements on accuracy and granularity. Abstract: The visibility of a traffic sign at night depends on its retro-reflectivity, a property that needs to be frequently monitored to ensure transportation safety. In the U.S., Federal Highway Administration (FHWA) maintains regulations to ensure minimum retro-reflectivity levels. Current measurement techniques either (a) use vehicle mounted device during the night, or (b) use manual handheld devices during the day. The former is expensive due to nighttime labor cost. The latter is time-consuming and unsafe. To address these limitations, this paper presents a computer vision-based technique to measure retro-reflectivity during daytime using a vehicle mounted device. The presented algorithms simulate nighttime visibility of traffic signs from images taken during daytime and measure their retro-reflectivity. The technique is faster, cheaper, and safer as it neither requires nighttime operation nor requires manual sign inspection. It also satisfies FHWA measurement guidelines both in terms of granularity and accuracy. The performance of the presented technique is evaluated under various testing conditions. The results are promising and demonstrate a strong potential in lowering inspection cost and improving safety in practical applications on retro-reflectivity measurement. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 29:Issue 4(2015:Oct.)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 29:Issue 4(2015:Oct.)
- Issue Display:
- Volume 29, Issue 4 (2015)
- Year:
- 2015
- Volume:
- 29
- Issue:
- 4
- Issue Sort Value:
- 2015-0029-0004-0000
- Page Start:
- 1028
- Page End:
- 1040
- Publication Date:
- 2015-10
- Subjects:
- Retro-reflectivity -- Traffic sign -- Image-based -- Remote sensing -- Computer vision
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2015.08.003 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 2323.xml