E2CAV, Pavement layer thickness estimation system based on image texture operators
Context: Public roads are an essential part of economic progress in any country; they are fundamental for increasing the efficiency on transportation of goods and are a remarkable source of employment. For its part, Colombia has few statistics on the condition of its roads; according with INVIAS the...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | Spanish |
Published: |
Universidad Distrital Francisco Jose de Caldas
2017-01-01
|
Series: | Tecnura |
Subjects: | |
Online Access: | http://revistas.udistrital.edu.co/ojs/index.php/Tecnura/article/view/10282 |
id |
doaj-05a866eb04f04b9ea50b937ce68f91c4 |
---|---|
record_format |
Article |
spelling |
doaj-05a866eb04f04b9ea50b937ce68f91c42020-11-24T22:45:35ZspaUniversidad Distrital Francisco Jose de CaldasTecnura2248-76380123-921X2017-01-012151819510.14483/udistrital.jour.tecnura.2017.1.a068748E2CAV, Pavement layer thickness estimation system based on image texture operatorsBrayan Barrios Arcila0Eval Bladimir Bacca Cortes1Sandra Nope Rodríguez2Universidad del ValleUniversidad del ValleUniversidad del ValleContext: Public roads are an essential part of economic progress in any country; they are fundamental for increasing the efficiency on transportation of goods and are a remarkable source of employment. For its part, Colombia has few statistics on the condition of its roads; according with INVIAS the state of the roads in Colombia can be classified as “Very Good” (21.1%), “Good” (34.7%), and “Regular” or “Bad” (43.46%). Thus, from the point of view of pavement rehabilitation, it is worth securing the quality of those roads classified as “Regular” or “Bad”. Objective: In this paper we propose a system to estimate the thickness of the pavement layer using image segmentation methods. The pavement thickness is currently estimated using radars of terrestrial penetration, extraction of cores or making pips; and it is part of structural parameters in the systems of evaluation of pavement. Method: The proposed system is composed of a vertical movement control unit, which introduces a video scope into a small hole in the pavement, then the images are obtained and unified in a laptop. Finally, this mosaic is processed through texture operators to estimate the thickness of the pavement. Users can select between the Otsu method and Gabor filters to process the image data. Results: The results include laboratory and field tests; these tests show errors of 5.03% and 11.3%, respectively, in the thickness of the pavement. Conclusion: The proposed system is an attractive option for local estimation of pavement thickness, with minimal structural damage and less impact on mobility and number of operators.http://revistas.udistrital.edu.co/ojs/index.php/Tecnura/article/view/10282Pavement layer, thickness estimation, Gabor filters, texture operators, Otsu |
collection |
DOAJ |
language |
Spanish |
format |
Article |
sources |
DOAJ |
author |
Brayan Barrios Arcila Eval Bladimir Bacca Cortes Sandra Nope Rodríguez |
spellingShingle |
Brayan Barrios Arcila Eval Bladimir Bacca Cortes Sandra Nope Rodríguez E2CAV, Pavement layer thickness estimation system based on image texture operators Tecnura Pavement layer, thickness estimation, Gabor filters, texture operators, Otsu |
author_facet |
Brayan Barrios Arcila Eval Bladimir Bacca Cortes Sandra Nope Rodríguez |
author_sort |
Brayan Barrios Arcila |
title |
E2CAV, Pavement layer thickness estimation system based on image texture operators |
title_short |
E2CAV, Pavement layer thickness estimation system based on image texture operators |
title_full |
E2CAV, Pavement layer thickness estimation system based on image texture operators |
title_fullStr |
E2CAV, Pavement layer thickness estimation system based on image texture operators |
title_full_unstemmed |
E2CAV, Pavement layer thickness estimation system based on image texture operators |
title_sort |
e2cav, pavement layer thickness estimation system based on image texture operators |
publisher |
Universidad Distrital Francisco Jose de Caldas |
series |
Tecnura |
issn |
2248-7638 0123-921X |
publishDate |
2017-01-01 |
description |
Context: Public roads are an essential part of economic progress in any country; they are fundamental for increasing the efficiency on transportation of goods and are a remarkable source of employment. For its part, Colombia has few statistics on the condition of its roads; according with INVIAS the state of the roads in Colombia can be classified as “Very Good” (21.1%), “Good” (34.7%), and “Regular” or “Bad” (43.46%). Thus, from the point of view of pavement rehabilitation, it is worth securing the quality of those roads classified as “Regular” or “Bad”.
Objective: In this paper we propose a system to estimate the thickness of the pavement layer using image segmentation methods. The pavement thickness is currently estimated using radars of terrestrial penetration, extraction of cores or making pips; and it is part of structural parameters in the systems of evaluation of pavement.
Method: The proposed system is composed of a vertical movement control unit, which introduces a video scope into a small hole in the pavement, then the images are obtained and unified in a laptop. Finally, this mosaic is processed through texture operators to estimate the thickness of the pavement. Users can select between the Otsu method and Gabor filters to process the image data.
Results: The results include laboratory and field tests; these tests show errors of 5.03% and 11.3%, respectively, in the thickness of the pavement.
Conclusion: The proposed system is an attractive option for local estimation of pavement thickness, with minimal structural damage and less impact on mobility and number of operators. |
topic |
Pavement layer, thickness estimation, Gabor filters, texture operators, Otsu |
url |
http://revistas.udistrital.edu.co/ojs/index.php/Tecnura/article/view/10282 |
work_keys_str_mv |
AT brayanbarriosarcila e2cavpavementlayerthicknessestimationsystembasedonimagetextureoperators AT evalbladimirbaccacortes e2cavpavementlayerthicknessestimationsystembasedonimagetextureoperators AT sandranoperodriguez e2cavpavementlayerthicknessestimationsystembasedonimagetextureoperators |
_version_ |
1725687799639703552 |