Skip to main content

Optimized Embedding and Decoding of Extrinsic Signatures for Electrophotographic Halftone Images

Buy Article:

$20.00 plus tax (Refund Policy)


Printer identification based on a printed document can provide forensic information to protect copyright and verify authenticity. In this work, a stochastic dot interaction model that take in to consideration of scanner characteristics and print-scan channel noise is developed to predict the impact of embedding extrinsic signatures using laser intensity modulation. With this model, reflectance of the printout can be effectively estimated without extensive measurements. In addition, we proposed an optimization framework to select the modulation parameters that will maximize the embedding capacity and detection reliability. Preliminary analysis results such as achievable capacity and correct detection rate are discussed.

Document Type: Research Article

Publication date: January 1, 2008

More about this publication?
  • For more than 25 years, NIP has been the leading forum for discussion of advances and new directions in non-impact and digital printing technologies. A comprehensive, industry-wide conference, this meeting includes all aspects of the hardware, materials, software, images, and applications associated with digital printing systems, including drop-on-demand ink jet, wide format ink jet, desktop and continuous ink jet, toner-based electrophotographic printers, production digital printing systems, and thermal printing systems, as well as the engineering capability, optimization, and science involved in these fields.

    Since 2005, NIP has been held in conjunction with the Digital Fabrication Conference.

  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Membership Information
  • Terms & Conditions
  • ingentaconnect is not responsible for the content or availability of external websites

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more