Document Type

Conference Proceeding

Publication Date



The microscopic details of printing often are unnoticed by humans, but can make differences that affect machine recognition of printed text. Models of the defects introduced into images by printing can be used to improve machine recognition. A probabilistic model used to generate images showing toner placement bears similarities to actual printed images. An equation derived for the average coverage of paper by toner particles having probabilistic placement is developed using geometric probability. Simulations show that averages of ‘printed images’ do have the same average coverage as the derived average coverage equations.

Copyright Statement

This document was originally published by CSREA/WORLDCOMP Press in WorldComp'14, July 21-14, Las Vegas, Nevada, USA, The 2014 World Congress in Computer Science and Computer Engineering and Applied Computing. Copyright restrictions may apply.