Abstract
In the development of system that can analyze image quality of a printed page, there is variability in
what the customer will consider unacceptable image quality for their print job. The algorithms, be them
expert rule based, deep learning, or some other AI variant, will output a value for the image quality that
fits within a range. The low end of that range is generally considered good image quality, while the high
end is considered poor image quality. With customer variance, any system employing the analysis of
image quality will have to take that variance in account. One way to account for this is to allow percustomer,
per‐device customization of the acceptable image quality threshold.
Creative Commons License
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Recommended Citation
INC, HP, "IMAGE QUALITY ANALYSIS CUSTOMIZATION FOR VARIANCE IN CUSTOMER SENSITIVITY", Technical Disclosure Commons, (November 21, 2018)
https://www.tdcommons.org/dpubs_series/1695