Resumen

BARRIOS ARCILA, Brayan; BACCA CORTES, Bladimir  y  NOPE RODRIGUEZ, Sandra. E2CAV, Pavement layer thickness estimation system based on image texture operators. Tecnura [online]. 2017, vol.21, n.51, pp.81-95. ISSN 0123-921X.  https://doi.org/10.14483/udistrital.jour.tecnura.2017.1.a06.

Abstract 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.

Palabras clave : Pavement layer; thickness estimation; Gabor filters; texture operators; Otsu.

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