%0 Journal Article
%T E2CAV, Pavement layer thickness estimation system based on image texture operators
%J -
%D 2017
%R https://doi.org/10.14483/udistrital.jour.tecnura.2017.1.a06
%X Resumen (en_US) 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. Resumen (es_ES) Contexto: Las carreteras p迆blicas son esenciales para el progreso econ車mico de cualquier pa赤s, ya que son fundamentales para el incremento en la eficiencia del transporte de bienes, y son una excelente fuente de empleo. Sin embargo, Colombia tiene pocas estad赤sticas sobre la condici車n de sus carreteras. e acuerdo con Inv赤as, el estado de las v赤as pavimentadas colombianas puede resumirse as赤: 21,1 % son clasificadas como ※Muy buenas§; 34,7 %, como ※Buenas§, y 43,46 %, como ※Regulares§ o ※Malas§. Entonces, desde el punto de vista de rehabilitaci車n de pavimentos, vale la pena asegurar la calidad de aquellas carreteras clasificadas como ※Regulares§ o ※Malas§. Objetivo: En este trabajo se propone un sistema para estimar el espesor de la capa de pavimento usando m谷todos de segmentaci車n de texturas en im芍genes. Actualmente, el espesor del pavimento es estimado usando radares de penetraci車n terrestre, extracci車n de n迆cleos o realizando apiques;
%K Pavement layer
%K thickness estimation
%K Gabor filters
%K texture operators
%K Otsu capa de pavimento
%K estimaci車n de espesor
%K filtros Gabor
%K operadores de textura
%K Otsu
%U https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/10282