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Iris Digital Watermarking

  • Reference work entry
  • First Online:
Encyclopedia of Biometrics

  • 176 Accesses

Synonyms

Biometric watermarking; Digital watermarking

Definition

Iris digital watermarking is a specific type of digital watermarking that involves the imperceptible embedding of data (the watermark) in iris images (the host) in order to impart additional security to an iris biometric system. The watermark data can be strings of random digits; system-specific identifiers, such as organization names and file creation dates; or biometric feature vectors. The additional security offered by the watermark may result from using it as a mechanism for proving the authenticity of the host image, tracking the chain of custody, or incorporating a multimodal biometric option. Iris digital watermarking or biometric watermarking, in general, is typically used in tandem with cryptography and, importantly, provides a layer of security that remains intact after the decryption process. A functional iris digital watermark should not degrade the performance of the host biometric system it protects.

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Author information

Authors and Affiliations

  1. Noblis, Inc., Falls Church, VA, USA

    Nick Bartlow

  2. West Virginia University, Morgantown, WV, USA

    Nathan Kalka

  3. Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA

    Bojan Cukic

  4. Michigan State University, East Lansing, MI, USA

    Arun Ross

Authors
  1. Nick Bartlow
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  2. Nathan Kalka
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  3. Bojan Cukic
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  4. Arun Ross
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Editor information

Editors and Affiliations

  1. Center for Biometrics and Security, Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Stan Z. Li

  2. Departments of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Anil K. Jain

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Bartlow, N., Kalka, N., Cukic, B., Ross, A. (2015). Iris Digital Watermarking. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_170

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