Kmeans Clustering Based Ink Mismatch Detection
- KHAWAJA Muhammad ALI ,
- Muhammad Shazaib ,
- Rida Nasir
Abstract
Forgery investigation and detection has been a relevant topic of
interest for human beings since ages. Important messages written and
transported by kings in old ages were sealed with signatures and stamps
to achieve this purpose. But with the advent of digital technology,
forgery detection has become even more important since tools for forgery
have become vast as well. In this paper a technique based on pixel
clustering has been introduced for detection of modification, alteration
or forgery done with a different ink color pen. Hyperspectral images are
used for ink mismatch detection in a handwritten note. We propose ink
classification based on pixel intensities values present in all the
bands of hyperspectral images of the handwritten note. Our proposed
technique is quite simple yet effective in detecting ink mismatch with
relatively high accuracy.