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A novel hyperspectral camera and analysis platform for the non-destructive material identification and mapping: An application in paintings by El Greco

机译:一种新型高光谱相机和非破坏性材料识别和测绘的分析平台:El Greco绘画中的应用

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Non-destructive point spectroscopic techniques and destructive methods based on sampling and ex-situ analysis are not efficient for examining large areas of objects of artistic and historic value. A novel hyperspectral camera and analysis platform (HySCAP) is presented in this paper, integrating innovative electrooptic solutions and advanced spectral analysis and classification algorithms. This combination offers and attractive alternative to a variety of destructive or ionizing methods used routinely for material identification. HySCAP acquires millions of reflectance and/or fluorescence spectra and tens of narrow band images, spanning the entire 370nm-1100nm wide spectral range. Specially developed and integrated into the HySCAP spectral analysis and system's training tools maximizes the obtained information with regard to the target-object's composition and structure. We have validated the HySCAP concept in a series of painting material replicas and in paintings belonging to El Greco's workshop, made by either the master himself or his students. Painting material replicas were developed following the original development processes and their fluorescence and reflectance spectra were measured and stored in the HySCAP's database. Some of them were used as training set and some other as validation set. The properly designed spectral analysis module was employed for handling the automated comparison of the training set of spectra with the spectra collected from the validation set of samples. Particularly, a series of algorithms for performing spectral comparison and classification were comparatively evaluated. It was found that the best performing algorithm was the Maximum Likelihood algorithm, which displayed accuracies within the range 80.3%-99.7% in identifying and mapping materials in El Greco's workshop paintings. The obtained results indicate that the HySCAP integrated approach emerges as a valuable scientific instrument for developing a series of more efficient methods in the broad field of nondestructive testing. In the particular case of the artwork analysis, which is presented in this paper, the offered new insight into the material composition, technique of construction, deterioration effects, authentication etc., are of essential importance in art history, in authentication and in determining the optimum preservation scheme.
机译:基于采样和前原位分析的非破坏性点光谱技术和破坏性方法对于检查艺术和历史价值的大面积而言是不效益的。本文提出了一种新型高光谱相机和分析平台(HYSCAP),集成了创新的电光解决方案和高级光谱分析和分类算法。这种组合提供和有吸引力的替代品种用于材料识别的各种破坏性或电离方法。 Hyscap获取数百万反射率和/或荧光光谱和数十个窄带图像,跨越整个370nm-1100nm宽的光谱范围。专门开发并集成到HYSCAP谱分析和系统的训练工具中,最大限度地提高了所获得的信息 - 目标对象的组成和结构。我们已经验证了一系列绘画材料复制品和属于埃尔格西哥研讨会的绘画,由硕士本人或他的学生制作。绘画材料复制品在原始开发过程之后开发,并测量其荧光和反射光谱并将其存储在Hyscap的数据库中。其中一些被用作培训集,一些其他作为验证集。采用正确设计的光谱分析模块来处理训练集的训练集的自动比较,并利用从验证集的样本集收集的光谱来处理。特别地,对用于执行光谱比较和分类的一系列算法进行了相对评价。发现,最好的执行算法是最大似然算法,其在EL Greco的车间绘画中识别和映射材料的范围内显示的精度为80.3%-99.7%。所获得的结果表明,HYSCAP综合方法作为开发一系列更有效的无损检测方法的有价值的科学仪器。在本文提出的艺术品分析的特殊情况下,对材料组成,建设技术,劣化效应,认证等的新洞察力在艺术史上至关重要,在认证和确定最佳保存方案。

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