Abstract
The discovery of ink mismatch provides important clues to
pre-writing examiners to indicate whether a particular manuscript is
written by a specific pen, or if a particular part of a note (e.g.,
signature) is written on a different ink compared to any other ink. In
this paper, we show that the hyperspectral image (HSI) of the
handwritten notes differs between visually similar inks. For this
purpose, we have created the first hyperspectral data domain for a
handwritten image in various blue and black inks, containing 33 visual
reference bands. In unsupervised clustering technique, visual responses
of inks fall into different groups to allow the separation of two
different inks from the text of the questions. The same method when used
in the RGB scan of these outputs fails to accurately distinguish the ink
because it is very difficult to separate the ink from the optical range.
HSI overcomes RGB deficiencies and allows better discrimination between
inks.
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