Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework

Weibao Wang; Gary Overall; Travis Riggs; Rebecca Silveston-Keith; Julie Whitney; George Chiu; Jan P. Allebach

doi:10.1117/12.2008428

4 February 2013 Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework

Weibao Wang, Gary Overall, Travis Riggs, Rebecca Silveston-Keith, Julie Whitney, George Chiu, Jan P. Allebach

Author Affiliations +

Proceedings Volume 8653, Image Quality and System Performance X; 86530P (2013) https://doi.org/10.1117/12.2008428
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric: linear regression and the support vector machine. We have implemented the image quality ruler, based on the recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and 20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages to train the two different predictors - one based on linear regression and the other based on the support vector machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.

Citation Download Citation

Weibao Wang, Gary Overall, Travis Riggs, Rebecca Silveston-Keith, Julie Whitney, George Chiu, and Jan P. Allebach "Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework", Proc. SPIE 8653, Image Quality and System Performance X, 86530P (4 February 2013); https://doi.org/10.1117/12.2008428

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