  Hyperspectral 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.
