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Volume: 33 | Article ID: art00006
Banding defect detection and image quality classification
  DOI :  10.2352/ISSN.2470-1173.2021.16.COLOR-245  Published OnlineJanuary 2021

Banding has been regarded as one of the most severe defects affecting the overall image quality in the printing industry. There has been a lot of research on it, but most of them focused on uniform pages or specific test images. Aiming at detecting banding on customer’s content pages, this paper proposes a banding processing pipeline that can automatically detect banding, identify periodic and isolated banding, and estimate the periodic interval. In addition, based on the detected banding characteristics, the pipeline predicts the overall quality of printed customer’s content pages and obtains predictions similar to human perceptual assessment.

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Yi Yang, Eric Maggard, Yousun Bang, Minki Cho, Jan P. Allebach, "Banding defect detection and image quality classificationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Color Imaging XXVI: Displaying, Processing, Hardcopy, and Applications,  2021,  pp 245-1 - 245-9,

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