Forgery Detection in a Questioned Hyperspectral Document Image using
AbstractHyperspectral imaging allows for analysis of images in several hundred
of spectral bands depending on the spectral resolution of the imaging
sensor. Hyperspectral document image is the one which has been captured
by a hyperspectral camera so that the document can be observed in the
different bands on the basis of their unique spectral signatures. To
detect the forgery in a document various Ink mismatch detection
techniques based on hyperspectral imaging have presented vast potential
in differentiating visually similar inks. Inks of different materials
exhibit different spectral signature even if they have the same color.
Hyperspectral analysis of document images allows identification and
discrimination of visually similar inks. Based on this analysis forensic
experts can identify the authenticity of the document. In this paper an
extensive ink mismatch detection technique is presented which uses KMean
Clustering to identify different inks on the basis of their unique
spectral response and separates them into different clusters.