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Proceedings Paper

Fine grained recognition of masonry walls for built heritage assessment
Author(s): Noelia Oses; F. Dornaika; Abdelmalik Moujahid
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Paper Abstract

This paper presents the ground work carried out to achieve automatic fine grained recognition of stone masonry. This is a necessary first step in the development of the analysis tool. The built heritage that will be assessed consists of stone masonry constructions and many of the features analysed can be characterized according to the geometry and arrangement of the stones. Much of the assessment is carried out through visual inspection. Thus, we apply image processing on digital images of the elements under inspection. The main contribution of the paper is the performance evaluation of the automatic categorization of masonry walls from a set of extracted straight line segments. The element chosen to perform this evaluation is the stone arrangement of masonry walls. The validity of the proposed framework is assessed on real images of masonry walls using machine learning paradigms. These include classifiers as well as automatic feature selection.

Paper Details

Date Published: 8 February 2015
PDF: 10 pages
Proc. SPIE 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques, 94060I (8 February 2015); doi: 10.1117/12.2078288
Show Author Affiliations
Noelia Oses, Zain Foundation (Spain)
F. Dornaika, Univ. of the Basque Country (Spain)
Basque Foundation for Science (Spain)
Abdelmalik Moujahid, Univ. del País Vasco (Spain)

Published in SPIE Proceedings Vol. 9406:
Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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