Skip to main content
Article
Statistical Image Differences, Degradation Features, and Character Distance Metrics
International Journal of Document Analysis and Recognition
  • Elisa Barney Smith, Boise State University
  • Xiaohui Qiu, Nanjing University of Post and Telecommunication
Document Type
Article
Publication Date
2-6-2004
DOI
http://dx.doi.org/10.1007/s10032-003-0117-9
Abstract

Document image quality is degraded through processes such as scanning, printing, and photocopying. The resulting bilevel image degradations can be categorized based either on observable degradation features or on degradation model parameters. The image degradation features can be related mathematically to model parameters. In this paper we statistically compare pairs of populations of degraded character images created with different model parameters. The probability that the character populations were degraded by the same model parameters correlates with the relationship between observable degradation features and the model parameters. Two metrics of character difference are used: Hamming distance and moment feature distance. Knowledge about the conditions under which characters will be similar and when they will be different can influence the choice of parameters for future experiments.

Copyright Statement

This is an author-produced, peer-reviewed version of this article. The final publication is available at www.springerlink.com. Copyright restrictions may apply. DOI: 10.1007/s10032-003-0117-9

Citation Information
Elisa Barney Smith and Xiaohui Qiu. "Statistical Image Differences, Degradation Features, and Character Distance Metrics" International Journal of Document Analysis and Recognition (2004)
Available at: http://works.bepress.com/elisa_barney_smith/127/