Electrophotographic (EP) print banding, jitter, and ghosting artifacts are common sources of print quality degradation. Traditionally, the characterization of banding and jitter artifacts relies mainly on the assumption that the defect has either a horizontal or vertical orientation which permits the simple 1-D analysis of the defect profile. However, this assumption can easily be violated if a small amount of printer or scanner skew is introduced to the analyzed images. In some cases, the defect can inherently be neither vertical nor horizontal. In this case, unless the defect orientation has been accurately detected before analysis, the 1-D-based approaches could bias the estimation of the defect severity. In this paper, we present an approach to characterize the jitter and banding artifacts of unrestricted orientation using wavelet filtering and 2-D spectral analysis. We also present a new system for detecting and quantifying ghosting defects. It includes a design for a printed test pattern to emphasize the ghosting defect and facilitate further processing and analysis. Wavelet filtering and a template matching technique are used to detect the ghost location along and across the scanned test pattern. A new metric is developed to quantify ghosting based upon its contrast, shape, and location consistency. Our experimental results show that the proposed approaches provide objective measures that quantify EP defects with a rank ordering correlation coefficient of 0.8 to 0.98, as compared to the subjective assessment of print quality experts.

Ghosting is a common print defect in electrophotographic printing. Printers experiencing ghosting defects show repeated images (residual images) of previously printed contents in the paper process direction. Detecting the residual image (ghost) location and contrast provides necessary information about the ghosting source and severity. In this paper, we present a new system for detecting and quantifying the ghosting defect. It includes a design for a printed test pattern to emphasize the ghosting defect and facilitate further processing and analysis. Wavelet filtering and a template matching technique are used to detect the ghost location along and across the scanned test pattern. A new metric is developed to quantify ghosting based on its contrast, shape, and location consistency. Experimental results on 31 samples of various types of ghosting showed 0.95 correlation between the proposed method's ranking and experts' visual ranking.