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Proceedings Paper

Experimental study of canvas characterization for paintings
Author(s): Bruno Cornelis; Ann Dooms; Adrian Munteanu; Jan Cornelis; Peter Schelkens
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Paper Abstract

The work described here fits in the context of a larger project on the objective and relevant characterization of paintings and painting canvas through the analysis of multimodal digital images. We captured, amongst others, X-ray images of different canvas types, characterized by a variety of textures and weave patterns (fine and rougher texture; single thread and multiple threads per weave), including raw canvas as well as canvas processed with different primers. In this paper, we study how to characterize the canvas by extracting global features such as average thread width, average distance between successive threads (i.e. thread density) and the spatial distribution of primers. These features are then used to construct a generic model of the canvas structure. Secondly, we investigate whether we can identify different pieces of canvas coming from the same bolt. This is an important element for dating, authentication and identification of restorations. Both the global characteristics mentioned earlier and some local properties (such as deviations from the average pattern model) are used to compare the "fingerprint" of different pieces of cloth coming from the same or different bolts.

Paper Details

Date Published: 4 February 2010
PDF: 12 pages
Proc. SPIE 7531, Computer Vision and Image Analysis of Art, 753103 (4 February 2010); doi: 10.1117/12.838345
Show Author Affiliations
Bruno Cornelis, Vrije Univ. Brussel (Belgium)
Ann Dooms, Vrije Univ. Brussel (Belgium)
Adrian Munteanu, Vrije Univ. Brussel (Belgium)
Jan Cornelis, Vrije Univ. Brussel (Belgium)
Peter Schelkens, Vrije Univ. Brussel (Belgium)


Published in SPIE Proceedings Vol. 7531:
Computer Vision and Image Analysis of Art
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)

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