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Assessment of segmentation methods for pore detection in cellular concrete images
dc.creator | Gaviria-Hdz J.F. | |
dc.creator | Medina L.J. | |
dc.creator | Mera C. | |
dc.creator | Chica L. | |
dc.creator | Sepúlveda-Cano L.M. | |
dc.date | 2019 | |
dc.date.accessioned | 2021-02-05T14:59:02Z | |
dc.date.available | 2021-02-05T14:59:02Z | |
dc.identifier.isbn | 9781728114910 | |
dc.identifier.uri | http://hdl.handle.net/11407/6060 | |
dc.description | 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. © 2019 IEEE. | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
dc.relation.isversionof | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068066499&doi=10.1109%2fSTSIVA.2019.8730220&partnerID=40&md5=c28abd489046fd91f7f9f191f9ec7e5a | |
dc.source | 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings | |
dc.subject | Cellular concrete | spa |
dc.subject | Fractional Derivative | spa |
dc.subject | Pore segmentation | spa |
dc.subject | Porosity estimation | spa |
dc.title | Assessment of segmentation methods for pore detection in cellular concrete images | |
dc.type | Conference Paper | eng |
dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | |
dc.publisher.program | Ingeniería de Telecomunicaciones | spa |
dc.identifier.doi | 10.1109/STSIVA.2019.8730220 | |
dc.subject.keyword | Concretes | eng |
dc.subject.keyword | Edge detection | eng |
dc.subject.keyword | Porosity | eng |
dc.subject.keyword | Vision | eng |
dc.subject.keyword | Cellular concretes | eng |
dc.subject.keyword | Edge detection methods | eng |
dc.subject.keyword | Fractional derivatives | eng |
dc.subject.keyword | High resolution image | eng |
dc.subject.keyword | Mercury porosimetry | eng |
dc.subject.keyword | Porosity estimation | eng |
dc.subject.keyword | Segmentation methods | eng |
dc.subject.keyword | Vacuum saturation | eng |
dc.subject.keyword | Image segmentation | eng |
dc.publisher.faculty | Facultad de Ingenierías | spa |
dc.affiliation | Gaviria-Hdz, J.F., Facultad de Ciencias Básicas, Universidad de Medellín, Medellín, Colombia | |
dc.affiliation | Medina, L.J., Facultad de Ciencias Básicas, Universidad de Medellín, Medellín, Colombia | |
dc.affiliation | Mera, C., Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín, Colombia | |
dc.affiliation | Chica, L., Facultad de Ingenierías, Universidad de Medellín, Medellín, Colombia | |
dc.affiliation | Sepúlveda-Cano, L.M., Facultad de Ingenierías, Universidad de Medellín, Medellín, Colombia | |
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dc.type.version | info:eu-repo/semantics/publishedVersion | |
dc.type.driver | info:eu-repo/semantics/other |
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