A hyperspectral unmixing approach for ink mismatch detection in unbalanced clusters

A hyperspectral unmixing approach for ink mismatch detection in unbalanced clusters

Detecting ink mismatch is a significant challenge in verifying the authenticity of documents, especially when dealing with uneven ink distribution. Conventional imaging methods frequently fail to distinguish visually similar inks. Our study presents a novel hyperspectral unmixing approach to detect...

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Bibliographic Details
Main Authors: Faryal Aurooj Nasir, Salman Liaquat, Khurram Khurshid, Nor Muzlifah Mahyuddin
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-03-01
Series:Journal of Information and Intelligence
Subjects:
k-means clustering
Gaussian mixture model (GMM)
Hyper spectral imaging (HSI)
iVision handwritten hyperspectral images dataset (HHID)
Document forensics
Online Access:http://www.sciencedirect.com/science/article/pii/S2949715924000040
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http://www.sciencedirect.com/science/article/pii/S2949715924000040

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