Paper
8 February 2015 Autonomous detection of ISO fade point with color laser printers
Ni Yan, Eric Maggard, Roberta Fothergill, Renee J. Jessome, Jan P. Allebach
Author Affiliations +
Proceedings Volume 9396, Image Quality and System Performance XII; 93960F (2015) https://doi.org/10.1117/12.2078324
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Image quality assessment is a very important field in image processing. Human observation is slow and subjective, it also requires strict environment setup for the psychological test 1. Thus developing algorithms to match desired human experiments is always in need. Many studies have focused on detecting the fading phenomenon after the materials are printed, that is to monitor the persistence of the color ink 2-4. However, fading is also a common artifact produced by printing systems when the cartridges run low. We want to develop an automatic system to monitor cartridge life and report fading defects when they appear. In this paper, we first describe a psychological experiment that studies the human perspective on printed fading pages. Then we propose an algorithm based on Color Space Projection and K-means clustering to predict the visibility of fading defects. At last, we integrate the psychological experiment result with our algorithm to give a machine learning tool that monitors cartridge life.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ni Yan, Eric Maggard, Roberta Fothergill, Renee J. Jessome, and Jan P. Allebach "Autonomous detection of ISO fade point with color laser printers", Proc. SPIE 9396, Image Quality and System Performance XII, 93960F (8 February 2015); https://doi.org/10.1117/12.2078324
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Printing

Diagnostics

Image segmentation

Machine learning

Image quality

Algorithm development

Acquisition tracking and pointing

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