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Porras Díaz, Hernán Castañeda Pinzon, Eduardo Alberto Sanabria Echeverry, Duván Yahír Medina Peréz, Gepthe Manuel 2018-11-20T20:23:21Z 2018-11-20T20:23:21Z 2012-10-31 Porras Díaz, H., Castañeda Pinzón, E., Sanabria Echeverry, D., & Medina Pérez, G. (2012). Detección automática de grietas de pavimento asfáltico aplicando características geométricas y descriptores de forma. INGE CUC, 8(1), 261-280. Recuperado a partir de https://revistascientificas.cuc.edu.co/ingecuc/article/view/265 0122-6517, 2382-4700 electrónico https://hdl.handle.net/11323/1500 2382-4700 Corporación Universidad de la Costa 0122-6517 REDICUC - Repositorio CUC https://repositorio.cuc.edu.co/ Las grietas son el principal daño en la superficie del pavimento, porque de estas se derivan los demás tipos de deterioros. La mayoría de grietas en imágenes de pavimento se encuentran con objetos no deseados y desconectadas. Para resolver este problema, se aplica el filtro mediana, para el suavizado de la imagen; el ajuste de contraste, para realzar la grieta; la segmentación, aplicando la media y la desviación estándar de los niveles de gris, para delimitar las grietas; el procesamiento morfológico, para fusionar separaciones estrechas; la eliminación de grietas falsas, aplicando características geométricas y descriptores de forma; y la conexión de grietas, para obtener grietas continuas. Los resultados experimentales fueron obtenidos de las imágenes de pavimento captadas por el sistema semiautomático y el algoritmo generador implementado. Las pruebas demostraron que las grietas fueron detectadas, con una sensibilidad de 81,72% y una especificidad de 99,96% para las imágenes captadas Cracks are the main damage to the surface of the pavement, because these are the other types of damage. Most cracks in pavement images encounter unwanted and disconnected objects. To solve this problem, the medium filter is applied, for smoothing the image; the contrast adjustment, to enhance the crack; the segmentation, applying the mean and the standard deviation of the gray levels, to delimit the cracks; morphological processing, to merge narrow separations; the elimination of false cracks, applying geometrical characteristics and shape descriptors; and the connection of cracks, to obtain continuous cracks. The experimental results were obtained from the pavement images captured by the semiautomatic system and the implemented generator algorithm. The tests showed that the cracks were detected, with a sensitivity of 81.72% and a specificity of 99.96% for the images captured Porras Díaz, Hernán Castañeda Pinzon, Eduardo Alberto Sanabria Echeverry, Duván Yahír Medina Peréz, Gepthe Manuel application/pdf spa Corporación Universidad de la Costa INGE CUC; Vol. 8, Núm. 1 (2012) INGE CUC INGE CUC [1] L. 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Mahgoub, “Asphalt Crack Detection Using Thermography”. Inframation: Thermal Imaging’s Leading Users Conference, 2005. pp. 1-12 INGE CUC INGE CUC https://revistascientificas.cuc.edu.co/ingecuc/article/view/265 Ajuste de contraste Características geométricas y descriptores de forma Corrección de intensidad Detección de grietas Eliminación de ruido Operaciones morfológicas Contrast adjustment Geometric characteristics and shape descriptors Intensity correction Crack detection Elimination of noise Morphological operations Detección automática de grietas de pavimento asfáltico aplicando características geométricas y descriptores de forma Automatic asphalt pavement crack detection using geometric features and shape descriptors Artículo de revista http://purl.org/coar/resource_type/c_6501 Text info:eu-repo/semantics/article http://purl.org/redcol/resource_type/ART info:eu-repo/semantics/acceptedVersion http://purl.org/coar/version/c_ab4af688f83e57aa info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 Publicationopen.access