Identifying leather type and authenticity by optical coherence tomography
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 7 November 2023
Issue publication date: 13 February 2024
Abstract
Purpose
This study aims to identify leather type and authenticity through optical coherence tomography.
Design/methodology/approach
Optical coherence tomography images taken from genuine and faux leather samples were used to create an image dataset, and automated machine learning algorithms were also used to distinguish leather types.
Findings
The optical coherence tomography scan results in a different image based on leather type. This information was used to determine the leather type correctly by optical coherence tomography and automatic machine learning algorithms. Please note that this system also recognized whether the leather was genuine or synthetic. Hence, this demonstrates that optical coherence tomography and automatic machine learning can be used to distinguish leather type and determine whether it is genuine.
Originality/value
For the first time to the best of the authors' knowledge, spectral-domain optical coherence tomography and automated machine learning algorithms were applied to identify leather authenticity in a noncontact and non-invasive manner. Since this model runs online, it can readily be employed in automated quality monitoring systems in the leather industry. With recent technological progress, optical coherence tomography combined with automated machine learning algorithms will be used more frequently in automatic authentication and identification systems.
Keywords
Citation
Sabuncu, M. and Özdemir, H. (2024), "Identifying leather type and authenticity by optical coherence tomography", International Journal of Clothing Science and Technology, Vol. 36 No. 1, pp. 1-16. https://doi.org/10.1108/IJCST-11-2022-0159
Publisher
:Emerald Publishing Limited
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