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Measuring and Evaluating Bitumen Coverage of Stones using two Different Digital Image Analysis Methods

Källén, Hanna LU ; Heyden, Anders LU ; Åström, Karl LU and Lindh, Per (2016) In Measurement 84(April 2016). p.56-67
Abstract
The most used pavement for paved roads in the world is asphalt. It is therefore important that the asphalt is as durable as possible to avoid expensive repairs of the roads. One important factor of the durability of the road is the adherence between the stones and the bitumen that holds the stones together. The affinity is tested by the so called rolling bottle test, where one put stones covered in bitumen in a bottle with water and let it roll on a bottle rolling machine. After a while the degree of bitumen coverage is estimated. In this paper, a method to estimate the degree of bitumen coverage using image analysis has been developed instead of the manual estimation that is used today. The presented method works for all colors of the... (More)
The most used pavement for paved roads in the world is asphalt. It is therefore important that the asphalt is as durable as possible to avoid expensive repairs of the roads. One important factor of the durability of the road is the adherence between the stones and the bitumen that holds the stones together. The affinity is tested by the so called rolling bottle test, where one put stones covered in bitumen in a bottle with water and let it roll on a bottle rolling machine. After a while the degree of bitumen coverage is estimated. In this paper, a method to estimate the degree of bitumen coverage using image analysis has been developed instead of the manual estimation that is used today. The presented method works for all colors of the stones and is based on the fact that bitumen reflects light much better than raw stones. A turntable that is rotated somewhat between images is used together with a light source in shape of a quarter of a circle to get as much specular reflections as possible. Then the amount of detected reflections is used to estimate the degree of bitumen coverage. To be able to compare the result with something close to ground truth, the method has been evaluated on lighter stones and compared with a second image analysis method that works well for lighter stones, and the results are promising. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Machine Vision, Bitumen Coverage, Specular Reflections, Segmentation
in
Measurement
volume
84
issue
April 2016
pages
12 pages
publisher
Elsevier
external identifiers
  • Scopus:84958757317
ISSN
0263-2241
DOI
10.1016/j.measurement.2016.02.007
language
English
LU publication?
yes
id
d9e0659d-cba2-43fb-a688-831e2d327446
date added to LUP
2016-04-12 12:23:14
date last changed
2016-10-13 05:06:01
@misc{d9e0659d-cba2-43fb-a688-831e2d327446,
  abstract     = {The most used pavement for paved roads in the world is asphalt. It is therefore important that the asphalt is as durable as possible to avoid expensive repairs of the roads. One important factor of the durability of the road is the adherence between the stones and the bitumen that holds the stones together. The affinity is tested by the so called rolling bottle test, where one put stones covered in bitumen in a bottle with water and let it roll on a bottle rolling machine. After a while the degree of bitumen coverage is estimated. In this paper, a method to estimate the degree of bitumen coverage using image analysis has been developed instead of the manual estimation that is used today. The presented method works for all colors of the stones and is based on the fact that bitumen reflects light much better than raw stones. A turntable that is rotated somewhat between images is used together with a light source in shape of a quarter of a circle to get as much specular reflections as possible. Then the amount of detected reflections is used to estimate the degree of bitumen coverage. To be able to compare the result with something close to ground truth, the method has been evaluated on lighter stones and compared with a second image analysis method that works well for lighter stones, and the results are promising.},
  author       = {Källén, Hanna and Heyden, Anders and Åström, Karl and Lindh, Per},
  issn         = {0263-2241},
  keyword      = {Machine Vision,Bitumen Coverage,Specular Reflections,Segmentation},
  language     = {eng},
  number       = {April 2016},
  pages        = {56--67},
  publisher    = {ARRAY(0x7ac8f00)},
  series       = {Measurement},
  title        = {Measuring and Evaluating Bitumen Coverage of Stones using two Different Digital Image Analysis Methods},
  url          = {http://dx.doi.org/10.1016/j.measurement.2016.02.007},
  volume       = {84},
  year         = {2016},
}