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New Trends in Databases and Information Systems pp 373–381Cite as

Data Mining Approach to Digital Image Processing in Old Painting Restoration

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 185))

Abstract

In this paper an attempt has been made to apply data mining techniques to the task of separation and categorization features in digital images of artworks. Both craquelure separation and retouching identification are important steps in art restoration process. Since the main goal is to enable recognition of character and cause of damage, as well as forecasting its further enlargement, a proper tool for precise detection of the pattern is needed. However, the complex nature of the pattern is a reason why a simple, universal detection algorithm is not always possible to implement. Algorithms presented in this work apply mining structures which depend of expandable set of attributes forming a feature vector, and thus offer an elastic structure for analysis.

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Authors and Affiliations

  1. University of Bielsko-Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Joanna Gancarczyk

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  1. Joanna Gancarczyk
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Correspondence to Joanna Gancarczyk .

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Editors and Affiliations

  1. , Department of Computer Science, Eindhoven University of Technology, Eindhoven, 5600, Netherlands

    Mykola Pechenizkiy

  2. Institute of Computing Science, Poznan University of Technology, ul. Piotrowo 2, Poznan, 60-965, Poland

    Marek Wojciechowski

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Gancarczyk, J. (2013). Data Mining Approach to Digital Image Processing in Old Painting Restoration. In: Pechenizkiy, M., Wojciechowski, M. (eds) New Trends in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32518-2_35

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  • DOI: https://doi.org/10.1007/978-3-642-32518-2_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32517-5

  • Online ISBN: 978-3-642-32518-2

  • eBook Packages: EngineeringEngineering (R0)

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