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Proceedings Paper

Hyperspectral imaging based techniques in ornamental stone characterization
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Paper Abstract

Ornamental stones are usually utilized for many purposes, ranging from structural to aesthetic ones. In this wide range of utilization, many different industrial sectors are involved. For all of them it is very important, at a different level, that these materials satisfy not only specific physical-chemical-mechanical requirements, but also some attributes that are much more difficult to quantify, that is those attributes strictly related to the final pictorial aspect of the stone manufactured goods. Stone pictorial-aesthetic characteristics are strongly influenced by stone surface status, that is by the surfaces reflectance properties. Such a property depends from stone compositional-textural characteristics and from the working procedures applied. The first set of attributes are related to stone mineral composition and their micro/macro arrangement, the others are related to the tools utilized and the actions applied in terms of operation sequence and workers knowledge-expertise. Each stone and each macro-operation carried out lead to a stone product whose finishing has to follow a specific rule: "optimal" polishing procedures for a stone can lead to very poor results for others. The study was addressed to evaluate the possibility to introduce a new hyperspectral imaging based approach to quantify the level of polishing of stone products and, at the same time, trying to perform also a pictorial-aesthetic characterization trough the identification of natural and/or working defects.

Paper Details

Date Published: 8 November 2005
PDF: 12 pages
Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 59960N (8 November 2005); doi: 10.1117/12.629426
Show Author Affiliations
Giuseppe Bonifazi, Univ. degli Studi di Roma La Sapienza (Italy)
Silvia Serranti, Univ. degli Studi di Roma La Sapienza (Italy)
Paolo Menesatti, Istituto Sperimentale per la Meccanizzazione Agricola (Italy)

Published in SPIE Proceedings Vol. 5996:
Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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