Scanning Micro X-ray Fluorescence and Multispectral Imaging Fusion: A Case Study on Postage Stamps

被引:1
|
作者
Gerodimos, Theofanis [1 ]
Patakiouta, Ioanna Vasiliki [1 ]
Papadakis, Vassilis M. [2 ,3 ]
Exarchos, Dimitrios [1 ]
Asvestas, Anastasios [1 ]
Kenanakis, Georgios [3 ]
Matikas, Theodore E. [1 ]
Anagnostopoulos, Dimitrios F. [1 ]
机构
[1] Univ Ioannina, Dept Mat Sci & Engn, Ioannina 45110, Greece
[2] Univ West Attica, Dept Ind Design & Prod Engn, Athens 12244, Greece
[3] Fdn Res & Technol, Inst Elect Struct & Laser, Hellas 70013, Greece
关键词
scanning micro-XRF; multispectral imaging; spectral images; dataset fusion; co-registration; k-means clustering; elemental and chemical analysis; postage stamps; material characterization; MA-XRF; PAINTINGS; ICON;
D O I
10.3390/jimaging10040095
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
Scanning micr omicron X-ray fluorescence (mu-XRF) and multispectral imaging (MSI) were applied to study philately stamps, selected for their small size and intricate structures. The mu-XRF measurements were accomplished using the M6 Jetstream Bruker scanner under optimized conditions for spatial resolution, while the MSI measurements were performed employing the XpeCAM-X02 camera. The datasets were acquired asynchronously. Elemental distribution maps can be extracted from the mu-XRF dataset, while chemical distribution maps can be obtained from the analysis of the multispectral dataset. The objective of the present work is the fusion of the datasets from the two spectral imaging modalities. An algorithmic co-registration of the two datasets is applied as a first step, aiming to align the multispectral and mu-XRF images and to adapt to the pixel sizes, as small as a few tens of micrometers. The dataset fusion is accomplished by applying k-means clustering of the multispectral dataset, attributing a representative spectrum to each pixel, and defining the multispectral clusters. Subsequently, the mu-XRF dataset within a specific multispectral cluster is analyzed by evaluating the mean XRF spectrum and performing k-means sub-clustering of the mu-XRF dataset, allowing the differentiation of areas with variable elemental composition within the multispectral cluster. The data fusion approach proves its validity and strength in the context of philately stamps. We demonstrate that the fusion of two spectral imaging modalities enhances their analytical capabilities significantly. The spectral analysis of pixels within clusters can provide more information than analyzing the same pixels as part of the entire dataset.
引用
收藏
页数:14
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