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Developed by Diego Sinitò.
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Coordinators
Filippo Stanco, Giovanni Puglisi, Germana Barone, Paolo Mazzoleni
Team
Description
The microscopic description of ancient pottery is widely used for the fabric de finition, classi fication and provenance assessment. In most cases, however, the description is qualitative. An improvement of the study of archaeological pottery needs a more objective approach with quantitative analysis.
In classical scienfiti c literature, the structural features and mineralogical composition of pottery are carried out on thin sections by means of transmitted polarized light microscope.
The determination were obtained through observations with and without cross polarizator (nicols). The quantitative measurements are normally achieved with tedious and time consuming table with point counter.
In this paper the attention has been focused on the automatic identifi cation of structural and textural components of the potteries through optical microscopy. Image analysis techniques have been then used to automatically classify the image components.
Results confi rm the effectiveness of the proposed approach: petrographic data collection becomes faster with respect to the traditional method providing also quantitative information useful for fabric recognition.
In classical scienfiti c literature, the structural features and mineralogical composition of pottery are carried out on thin sections by means of transmitted polarized light microscope.
The determination were obtained through observations with and without cross polarizator (nicols). The quantitative measurements are normally achieved with tedious and time consuming table with point counter.
In this paper the attention has been focused on the automatic identifi cation of structural and textural components of the potteries through optical microscopy. Image analysis techniques have been then used to automatically classify the image components.
Results confi rm the effectiveness of the proposed approach: petrographic data collection becomes faster with respect to the traditional method providing also quantitative information useful for fabric recognition.
Gallery
Publications
Puglisi, G. and Stanco, F. and Barone, G. and Mazzoleni, P., "Automatic extraction of petrographic features from pottery of archaeological interest". Journal on Computing and Cultural Heritage, Vol 8, No 3, DOI 10.1145/2700422, 2015.
Puglisi, G. and Stanco, F. and Barone, G. and Mazzoleni, P., "Automatic petrographic feature extraction from pottery of archaeological interest". International Symposium on Image and Signal Processing and Analysis, ISPA, pp. 548-551, DOI 10.1109/ispa.2013.6703801, 2013.
Sinitò, Diego and Verderame, Alessandro and Lombardo, Carmelo and Treffiletti, Alessandro and Fugazzotto, Maura and Allegra, Dario and Santarcangelo, Vito and Stanco, Filippo and Barone, Germana, "A Simulator for minero-petrographic and chemical research instruments". PatReCH workshop, ICPR, 2022.
Thesis
Marina Gangemi, "Riconoscimento automatico di sezioni sottili di ceramiche di interesse archeologico". Supervisor: G. Barone, F. Stanco, 2009.
Daniele Intravaia, "Il problema del riconoscimento automatico delle caratteristiche petrografiche in sezione sottile di ceramiche di interesse archeologico". Supervisor: F. Stanco, Assistant supervisor: G. Puglisi, G. Barone, P. Mazzoleni, 2012.
