Near-infrared hyperspectral imaging (NIR-HSI) and normalized difference image (NDI) data processing: An advanced...

Area of Science:

• Analytical Chemistry
• Bioarchaeology
• Imaging Spectroscopy

Background:

• Bioarchaeology relies on bone collagen for crucial chronological, paleoecological, and taxonomic data.
• Destructive analytical methods risk damaging limited and precious archaeological bone samples.
• There is a need for non-destructive methods to analyze collagen in large bone samples.

Purpose of the Study:

• To develop and validate a near-infrared hyperspectral imaging (NIR-HSI) method for collagen mapping in large bones.
• To provide semi-quantitative estimations of collagen content.
• To enable pre-screening of archaeological bone samples, minimizing destructive analysis.

Main Methods:

• Application of a Normalized Difference Image (NDI) approach to hyperspectral data.
• Pixel-wise computation of NDI values to localize collagen.
• Comparison of NDI values with reference samples for semi-quantitative analysis.

Main Results:

• Successful generation of spectral maps revealing collagen distribution in large bones.
• Demonstration of semi-quantitative collagen estimation capabilities.
• Validation of NIR-HSI as a non-destructive pre-screening tool.

Conclusions:

• The proposed NIR-HSI method offers an efficient and innovative approach for collagen analysis in bioarchaeology.
• This technique helps preserve valuable archaeological bone samples by reducing the need for destructive methods.
• NIR-HSI facilitates informed selection of sampling points, optimizing research efficiency and cost.