Abstract
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.