Hyperspectral document image processing : Applications, challenges and future prospects

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)12-22
Journal / PublicationPattern Recognition
Online published15 Jan 2019
Publication statusPublished - Jun 2019


Automatic image analysis is a crucial component of many intelligent systems designed for high-level understanding of documents. Most document image understanding systems are usually based on applying pattern recognition techniques to conventional three channel RGB images. Airborne and satellite based macro scale Hyperspectral Imaging (HSI) systems are well established for geosciences. Recently, owing to advancements in imaging speed and reduced camera costs, micro scale HSI systems are also gaining importance in ground based applications such as hyperspectral document image analysis. HSI is non destructive and offers new opportunities via measuring richer information along spectral dimension by imaging the document in contiguous bands across the electromagnetic spectrum. Hyperspectral document imaging has shown potential for solving many challenging problems of document image analysis including signature extraction, ink or document aging, information retrieval from historical document images, paintings and forensic analysis of documents. In this paper, we explore the potential of HSI for document image analysis and present a comprehensive review of the literature and future prospects. We highlight and discuss the challenges involved in the acquisition and processing of hyperspectral document images. A review of commercial HSI systems for document image analysis is also presented.

Research Area(s)

  • Cultural heritage, Historical document image analysis, Hyperspectral document imaging, Ink mismatch detection, Signature extraction

Citation Format(s)

Hyperspectral document image processing: Applications, challenges and future prospects. / Rizwan, Qureshi; Uzair, Muhammad; Khurshid, Khurram et al.
In: Pattern Recognition, Vol. 90, 06.2019, p. 12-22.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review