Skip to main content

An evaluation model for character quality on scanned image

Buy Article:

$20.00 plus tax (Refund Policy)


Scanners, standalone or embedded in MFP, have been widely utilized for document scanning/copying in office environments. There are many factors affecting the quality of scanned image. They include quality of characters, size of gamut, degree of noises, color reproduction, tone characteristics, and gray balance, etc. This paper is focused on quantitative evaluation of character quality on scanned images. Objective of this paper is to derive a quantitative evaluation model that faithfully matches with the human perception. Key attributes determining character quality are extracted first based on subjective human visual experiments. For each of the identified attributes, a quantitative metric is developed. The proposed evaluation model is designed as a linear combination of the quantified metrics. Coefficients for linear combination are estimated by applying linear regression. Various experiments are performed to verify the performance of the proposed evaluation model.

Document Type: Research Article

Publication date: 2008-01-01

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
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect 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