Building Material Recognition and Feature Extraction Using Small CCD Sensor and Image Analysis and Clustering Techniques

Authors

  • Stefano Pagnotta Author
  • Danis Ionut Filimon Author
  • Gianni Gallello Author
  • Marco Lezzerini Author

DOI:

https://doi.org/10.29227/IM-2024-01-25

Keywords:

material recognition, building material, feature extraction, ccd sensor, image analysis, clustering techniques

Abstract

Heritage Building material recognition is the process of classifying building materials based on their visual appearance. It is important in construction, urban planning, and archaeology. Image analysis is a common approach, starting with acquiring RGB images, then extracting features using techniques such as colour histograms and texture analysis, and clustering the materials into groups using algorithms like k - means. Finally, the materials are classified into categories using classifiers like decision trees, SVM, or neural networks. Image analysis is a useful tool for building material recognition, as it allows for accurate classification of building materials based on their visual characteristics .

Author Biographies

  • Stefano Pagnotta

    Department of Earth Sciences, University of Pisa, Via S. Maria 53 - 56126, Pisa, Italy; https://orcid.org/0000 - 0002 - 6645 - 4924

  • Danis Ionut Filimon

    Department of Earth Sciences, University of Pisa, Via S. Maria 53 - 56126, Pisa, Italy

  • Gianni Gallello

    Department of Prehistory, Archeology and Ancient History University of Valencia Av. Blasco Ibáñez 28 - 46010, Valencia, Spain; https://orcid.org/0000 - 0003 - 3641 - 8815

  • Marco Lezzerini

    Department of Earth Sciences, University of Pisa, Via S. Maria 53 - 56126, Pisa, Italy; https://orcid.org/0000 - 0001 - 9204 - 4462

Published

2024-07-01

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