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On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling pp 129–153Cite as

Cultural Heritage Applications: Archaeological Ceramics and Building Restoration

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Part of the book series: Springer Theses ((Springer Theses,volume 4))

Abstract

This chapter presents two applications: classification of archaeological ceramics and diagnosis of historic building restoration. In the first application, we consider the ICAMM-based algorithm proposed in Chap. 3 (Mixca) to model the joint-probability density of the features. This classifier is applied to a challenging novel application: classification of archaeological ceramics. ICAMM by Mixca gathers relevant characteristics that have general interest in the area of material classification. On one hand, it can deal with arbitrary forms of the underlying probability densities in the feature vector space as non-parametric methods can do. On the other hand, mutual dependences among the features are modelled in a parametric form so that ICAMM based on Mixca can achieve good performance even with a training set of relatively small size, which is characteristic of parametric methods.

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Authors and Affiliations

  1. Department of Communications, School of Telecommunication Engineering, Polytechnic University of Valencia, Camino de Vera s/n, 46022, Valencia, Spain

    Addisson Salazar

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  1. Addisson Salazar
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Salazar, A. (2013). Cultural Heritage Applications: Archaeological Ceramics and Building Restoration. In: On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling. Springer Theses, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30752-2_6

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  • DOI: https://doi.org/10.1007/978-3-642-30752-2_6

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  • Online ISBN: 978-3-642-30752-2

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