A Bayesian decision model for watercolour analysis

Vassiliki Kokla; Alexandra Psarrou; Vassilis Konstantinou

doi:10.1117/12.725666

16 July 2007 A Bayesian decision model for watercolour analysis

Vassiliki Kokla, Alexandra Psarrou, Vassilis Konstantinou

Proceedings Volume 6618, O3A: Optics for Arts, Architecture, and Archaeology; 66180S (2007) https://doi.org/10.1117/12.725666
Event: Optical Metrology, 2007, Munich, Germany

Abstract

Bayesian Classification methods can be applied to images of watercolour paintings in order to characterize blue and green pigments used in these paintings. Pigments found in watercolour paintings are semi-transparent materials and their analysis provides important information on the date, the painter, the place of the production of watercolour paintings and generally on the authenticity of these works of art. However, watercolour pigments are difficult to characterize because their intensity depends on the amount of liquid spread during painting and the reflective properties of the underlying support. The method describedin this paper is non-destructive, non invasive, does not involve sampling and can be applied in situ. The methodology is based on the photometric properties of pigments and produce computational models which classify diverse types of pigments found in watercolour paintings. These pigments are photographed in the visible and infrared area of electromagnetic spectrum and models based on statistical characteristics of intensity values using a mixture of Gaussian functions are created. Finally the pigments are classified using a Bayesian classification algorithm to process the generate models.

Citation Download Citation

Vassiliki Kokla, Alexandra Psarrou, and Vassilis Konstantinou "A Bayesian decision model for watercolour analysis", Proc. SPIE 6618, O3A: Optics for Arts, Architecture, and Archaeology, 66180S (16 July 2007); https://doi.org/10.1117/12.725666

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KEYWORDS

Infrared radiation

Visible radiation

Cobalt

Infrared imaging

Reflectivity

Statistical analysis

Thermal modeling

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