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Detection of thermal bridges from thermographic images by means of image processing approximation algorithms

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  • Asdrubali, Francesco
  • Baldinelli, Giorgio
  • Bianchi, Francesco
  • Costarelli, Danilo
  • Rotili, Antonella
  • Seracini, Marco
  • Vinti, Gianluca

Abstract

In this paper, we develop a procedure for the detection of the contours of thermal bridges from thermographic images, in order to study the energy performance of buildings. Two main steps of the above method are: the enhancement of the thermographic images by an optimized version of the mathematical algorithm for digital image processing based on the theory of sampling Kantorovich operators, and the application of a suitable thresholding based on the analysis of the histogram of the enhanced thermographic images. Finally, an improvement of the parameter defining the thermal bridge is obtained.

Suggested Citation

  • Asdrubali, Francesco & Baldinelli, Giorgio & Bianchi, Francesco & Costarelli, Danilo & Rotili, Antonella & Seracini, Marco & Vinti, Gianluca, 2018. "Detection of thermal bridges from thermographic images by means of image processing approximation algorithms," Applied Mathematics and Computation, Elsevier, vol. 317(C), pages 160-171.
    • Handle: RePEc:eee:apmaco:v:317:y:2018:i:c:p:160-171
    DOI: 10.1016/j.amc.2017.08.058
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    References listed on IDEAS

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    1. Baxhaku, Behar & Agrawal, Purshottam Narain, 2017. "Degree of approximation for bivariate extension of Chlodowsky-type q-Bernstein–Stancu–Kantorovich operators," Applied Mathematics and Computation, Elsevier, vol. 306(C), pages 56-72.
    2. Danilo Costarelli & Gianluca Vinti, 2017. "Convergence for a family of neural network operators in Orlicz spaces," Mathematische Nachrichten, Wiley Blackwell, vol. 290(2-3), pages 226-235, February.
    3. Francesco Bianchi & Anna Laura Pisello & Giorgio Baldinelli & Francesco Asdrubali, 2014. "Infrared Thermography Assessment of Thermal Bridges in Building Envelope: Experimental Validation in a Test Room Setup," Sustainability, MDPI, vol. 6(10), pages 1-14, October.
    4. Asdrubali, Francesco & Baldinelli, Giorgio & Bianchi, Francesco, 2012. "A quantitative methodology to evaluate thermal bridges in buildings," Applied Energy, Elsevier, vol. 97(C), pages 365-373.
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    Cited by:

    1. Costarelli, Danilo & Seracini, Marco & Vinti, Gianluca, 2020. "A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    2. Tiziana Basiricò & Antonio Cottone & Daniele Enea, 2020. "Analytical Mathematical Modeling of the Thermal Bridge between Reinforced Concrete Wall and Inter-Floor Slab," Sustainability, MDPI, vol. 12(23), pages 1-21, November.
    3. Coroianu, Lucian & Costarelli, Danilo & Gal, Sorin G. & Vinti, Gianluca, 2019. "The max-product generalized sampling operators: convergence and quantitative estimates," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 173-183.
    4. Iole Nardi & Elena Lucchi, 2023. "In Situ Thermal Transmittance Assessment of the Building Envelope: Practical Advice and Outlooks for Standard and Innovative Procedures," Energies, MDPI, vol. 16(8), pages 1-31, April.
    5. Kadak, Ugur, 2022. "Max-product type multivariate sampling operators and applications to image processing," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Mursaleen, M. & Naaz, Ambreen & Khan, Asif, 2019. "Improved approximation and error estimations by King type (p, q)-Szász-Mirakjan Kantorovich operators," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 175-185.
    7. David Bienvenido-Huertas & Juan Antonio Fernández Quiñones & Juan Moyano & Carlos E. Rodríguez-Jiménez, 2018. "Patents Analysis of Thermal Bridges in Slab Fronts and Their Effect on Energy Demand," Energies, MDPI, vol. 11(9), pages 1-18, August.
    8. Garrido, I. & Lagüela, S. & Otero, R. & Arias, P., 2020. "Thermographic methodologies used in infrastructure inspection: A review—Post-processing procedures," Applied Energy, Elsevier, vol. 266(C).
    9. Costarelli, D. & Krivoshein, A. & Skopina, M. & Vinti, G., 2019. "Quasi-projection operators with applications to differential-difference expansions," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.

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