Automatic Ink Mismatch Detection in Hyperspectral Images Using Kmeans Clustering.pdf (469.13 kB)Download file
Automatic Ink Mismatch Detection in Hyperspectral Images Using Kmeans Clustering.pdf
preprintposted on 2020-07-09, 04:16 authored by Muhammad TalhaMuhammad Talha, Noman Raza Shah, Fizza Imtiaz, Aneeqah Azmat
Hyper spectral imaging (HSI) is a technique that is used to obtain the spectrum for each pixel in the image. It helps in finding objects and identifying materials etc. Such an identification is very difficult using other imaging techniques. It allows the researchers to investigate the documents without any physical contact. Nowadays detection of unequal Ink mismatch based on HSI has shown vast improvement in distinguishing the inks. Detection of unequal Ink mismatch is an unbalanced clustering problem. This paper used K-means Clustering for ink mismatch detection. K-means Clustering find same subgroups in the data based on Euclidean distance. This paper demonstrates performance in unequal Ink mismatch based on HSI.
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Submitting Author's InstitutionInstitute of Space Technology, Islamabad
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