Paper
25 May 1998 Structural analysis of paintings based on brush strokes
Robert Sablatnig, Paul Kammerer, Ernestine Zolda
Author Affiliations +
Proceedings Volume 3315, Scientific Detection of Fakery in Art; (1998) https://doi.org/10.1117/12.308585
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
The origin of works of art can often not be attributed to a certain artist. Likewise it is difficult to say whether paintings or drawings are originals or forgeries. In various fields of art new technical methods are used to examine the age, the state of preservation and the origin of the materials used. For the examination of paintings, radiological methods like X-ray and infra-red diagnosis, digital radiography, computer-tomography, etc. and color analyzes are employed to authenticate art. But all these methods do not relate certain characteristics in art work to a specific artist -- the artist's personal style. In order to study this personal style of a painter, experts in art history and image processing try to examine the 'structural signature' based on brush strokes within paintings, in particular in portrait miniatures. A computer-aided classification and recognition system for portrait miniatures is developed, which enables a semi- automatic classification and forgery detection based on content, color, and brush strokes. A hierarchically structured classification scheme is introduced which separates the classification into three different levels of information: color, shape of region, and structure of brush strokes.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Sablatnig, Paul Kammerer, and Ernestine Zolda "Structural analysis of paintings based on brush strokes", Proc. SPIE 3315, Scientific Detection of Fakery in Art, (25 May 1998); https://doi.org/10.1117/12.308585
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Cited by 19 scholarly publications.
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KEYWORDS
Image segmentation

Sensors

Mathematical modeling

Eye

Image processing

Image classification

Nose

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