High resolution spectroscopic mapping imaging applied in situ to multilayer structures for stratigraphic identification of painted art objects

G. Karagiannis
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Abstract

The development of non–destructive techniques is a reality in the field of conservation science. These techniques are usually not so accurate, as the analytical micro–sampling techniques, however, the proper development of soft–computing techniques can improve their accuracy. In this work, we propose a real–time fast acquisition spectroscopic mapping imaging system that operates from the ultraviolet to mid infrared (UV/Vis/nIR/mIR) area of the electromagnetic spectrum and it is supported by a set of soft–computing methods to identify the materials that exist in a stratigraphic structure of paint layers. Particularly, the system acquires spectra in diffuse–reflectance mode, scanning in a Region-Of-Interest (ROI), and having wavelength range from 200 up to 5000 nm. Also, a fuzzy c–means clustering algorithm, i.e., the particular soft–computing algorithm, produces the mapping images. The evaluation of the method was tested on a byzantine painted icon.
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多层结构的原位高分辨率光谱成像在绘画艺术品地层识别中的应用
无损技术的发展是保护科学领域的现实。这些技术通常不像分析微采样技术那样精确,但适当发展软计算技术可以提高其准确性。在这项工作中,我们提出了一种实时快速采集光谱测绘成像系统,该系统从电磁波谱的紫外到中红外(UV/Vis/nIR/mIR)区域工作,并辅以一套软计算方法来识别存在于油漆层地层结构中的物质。特别是,该系统在漫反射模式下获取光谱,在感兴趣区域(ROI)扫描,波长范围从200到5000nm。此外,模糊c均值聚类算法,即特定的软计算算法,产生映射图像。该方法的评价是在一个拜占庭绘画图标上进行测试。
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