Assessment of segmentation methods for pore detection in cellular concrete images

Juan Fernando Gaviria-Hdz, Leidy Johanna Medina, Carlos Mera, Lina Chica, Lina María Sepúlveda-Cano

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferencia

Resumen

In the last years the use of cellular concretes has been extended due to the rise in the ratio strength/weight reached. Porosity is a property that must be taken into account because it is associated directly to the performance of a cellular concrete. The mercury porosimetry and vacuum saturation are test used to concrete porosity. However, these tests are expensive, and it requires a careful preparation of samples. Another way to determine porosity and pore distribution over concrete is reconstruction using high-resolution images from microscopy. As an alternative, in this work we compare traditional edge detection methods and fractional derivate method to detect the pores in images taken from a flat sample of cellular concrete. The experiments show that the method based on fractional derivate is more accurate to detect the pores, which is the first step to estimate total porosity of cellular concrete through non-specialized images.

Idioma originalInglés
Título de la publicación alojada2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728114910
DOI
EstadoPublicada - 1 abr 2019
Evento22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Bucaramanga, Colombia
Duración: 24 abr 201926 abr 2019

Serie de la publicación

Nombre2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

Conferencia

Conferencia22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
PaísColombia
CiudadBucaramanga
Período24/04/1926/04/19

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  • Citar esto

    Gaviria-Hdz, J. F., Medina, L. J., Mera, C., Chica, L., & Sepúlveda-Cano, L. M. (2019). Assessment of segmentation methods for pore detection in cellular concrete images. En 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings [8730220] (2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/STSIVA.2019.8730220