Manufacturing imperfections of photoconductor (PC) drums in electrophotographic (EP) printers cause low-
frequency artifacts that could produce objectionable non-uniformities in the final printouts. In this paper, we
propose a technique to detect and quantify PC artifacts. Furthermore, we spatially model the PC drum surface
for dynamic compensation of drum artifacts. After scanning printed pages of flat field areas, we apply a wavelet-
based filtering technique to the scanned images to isolate the PC-related artifacts from other printing artifacts,
based on the frequency, range, and direction of the PC defects. Prior knowledge of the PC circumference
determines the printed area at each revolution of the drum for separate analysis. Applied to the filtered images,
the expectation maximization (EM) algorithm models the PC defects as a mixture of Gaussians. We use the
estimated parameters of the Gaussians to measure the severity of the defect. In addition, a 2-D polynomial fitting
approach characterizes the spatial artifacts of the drum, by analyzing multiple revolutions of printed output.
The experimental results show a high correlation of the modeled artifacts from different revolutions of a drum.
This allows for generating a defect-compensating profile of the defective drum.
Print mottle is one of several attributes described in ISO/IEC DTS 24790, a draft technical specification for the measurement of image quality for monochrome printed output. It defines mottle as aperiodic fluctuations of lightness less than about 0.4 cycles per millimeter, a definition inherited from the latest official standard on printed image quality, ISO/IEC 13660. In a previous publication, we introduced a modification to the ISO/IEC 13660 mottle measurement algorithm that includes a band-pass, wavelet-based, filtering step to limit the contribution of high-frequency fluctuations including those introduced by print grain artifacts. This modification has improved the algorithm’s correlation with the subjective evaluation of experts who rated the severity of printed mottle artifacts. Seeking to improve upon the mottle algorithm in ISO/IEC 13660, the ISO 24790 committee evaluated several mottle metrics. This led to the selection of the above wavelet-based approach as the top candidate algorithm for inclusion in a future ISO/IEC standard. Recent experimental results from the ISO committee showed higher correlation between the wavelet-based approach and the subjective evaluation conducted by the ISO committee members based upon 25 samples covering a variety of printed mottle artifacts. In addition, we introduce an alternative approach for measuring mottle defects based on spatial frequency analysis of wavelet- filtered images. Our goal is to establish a link between the spatial-based mottle (ISO/IEC DTS 24790) approach and its equivalent frequency-based one in light of Parseval’s theorem. Our experimental results showed a high correlation between the spatial and frequency based approaches.
When evaluating printer resolution, addressability is a key consideration. Addressability defines the maximum number of spots or samples within a given distance, independent of the size of the spots when printed. Effective addressability is the addressability demonstrated by the final, printed output. It is the minimum displacement possible between the centers of printed objects. In this paper, we present a measurement procedure for effective addressability that offers an automated way to experimentally determine the addressability of the printed output. It requires printing, scanning, and measuring a test target. The effective addressability test target contains two types of elements, repeated to fill the page: fiducial lines and line segments. The fiducial lines serve as a relative reference for the incremental displacements of the individual line segments, providing a way to tolerate larger-scale physical distortions in the printer. An ordinary reflection scanner captures the printed test target. By rotating the page on the scanner, it is possible to measure effective addressability well beyond the scanner’s sampling resolution. The measurement algorithm computes the distribution of incremental displacements, forming either a unimodal or bimodal histogram. In the latter case, the mean of the second (non-zero) peak indicates the effective addressability. In the former case, the printer successfully rendered the target’s resolution, requiring another iteration of the procedure after increasing the resolution of the test target. The algorithm automatically estimates whether the histogram is unimodal or bimodal and computes parameters describing the quality of the measured histogram. Several experiments have refined the test target and measurement procedure, including two round-robin evaluations by the ISO WG4 committee. Results include an analysis of approximately 150 printed samples. The effective addressability attribute and measurement procedure are included in ISO/IEC TS 29112, a technical specification that describes the objective measurement of printer resolution for monochrome electrophotographic printers.
Grain is one of several attributes described in ISO/IEC TS 24790, a technical specification for the measurement of
image quality for monochrome printed output. It defines grain as aperiodic fluctuations of lightness greater than
0.4 cycles per millimeter, a definition inherited from the latest official standard on printed image quality, ISO/IEC
13660. Since this definition places no bounds on the upper frequency range, higher-frequency fluctuations (such
as those from the printer’s halftone pattern) could contribute significantly to the measurement of grain artifacts.
In a previous publication, we introduced a modification to the ISO/IEC 13660 grain measurement algorithm
that includes a band-pass, wavelet-based, filtering step to limit the contribution of high-frequency fluctuations.
This modification improves the algorithm’s correlation with the subjective evaluation of experts who rated the
severity of printed grain artifacts.
Seeking to improve upon the grain algorithm in ISO/IEC 13660, the ISO/IEC TS 24790 committee evaluated
several graininess metrics. This led to the selection of the above wavelet-based approach as the top candidate
algorithm for inclusion in a future ISO/IEC standard. Our recent experimental results showed r2 correlation
of 0.9278 between the wavelet-based approach and the subjective evaluation conducted by the ISO committee
members based upon 26 samples covering a variety of printed grain artifacts. On the other hand, our experiments
on the same data set showed much lower correlation (r2 = 0.3555) between the ISO/IEC 13660 approach and
the same subjective evaluation of the ISO committee members.
In addition, we introduce an alternative approach for measuring grain defects based on spatial frequency analysis
of wavelet-filtered images. Our goal is to establish a link between the spatial-based grain (ISO/IEC TS 24790)
approach and its equivalent frequency-based one in light of Parseval’s theorem. Our experimental results showed
r2 correlation near 0.99 between the spatial and frequency-based approaches.
In this paper, we propose a new technique to automatically restore the sharpness of blurred documents by
equalizing the frequency response of given scanners using linear filters. To measure the blur characteristics of
a scanning device, we measure its both horizontal and vertical Spatial Frequency Response (SFR). Starting
from the measured SFR of the scanning device, we design an equalizing filter so that the combined SFR of
the equalizing filter and the scanner resembles a perfect SFR. The desired 2D frequency response of the filter is
computed using linear interpolation of the horizontal and vertical responses derived from the corresponding SFRs
of the scanner. The filter design technique is two steps. First, a linear system of equations is constructed using
the unknown filter coefficients and the desired filter 2D frequency response. The linear least squares method is
used to solve the linear system of equations. The second step of the filter design uses a nonlinear optimization
technique to refine the results of the first step. Our experimental results show that this automated process can be
applied to different document scanning devices to equalize their spatial frequency response resulting in consistent
output sharpness levels.
Ordered halftone patterns in the original document interact with the periodic sampling of the scanner, producing
objectionable moir´e patterns. These are exacerbated when the copy is reprinted with an ordered halftone pattern.
A simple, small low-pass filter can be used to descreen the image and to correct the majority of moir´e artifacts.
Unfortunately, low-pass filtering affects detail as well, blurring it even further. Adaptive nonlinear filtering based
on image features such as the magnitude and the direction of image gradient can also be used. However, non
careful tuning of such filters could either cause damage to small details while descreeing the halftone areas,
or result in less descreening while sharpening small details. In this paper, we present a new segmentation-based
descreening technique. Scanned images are segmented into text, images and halftone classes using a
multiresolution classification of edge features. The segmentation results guide a nonlinear, adaptive filter to
favor sharpening or blurring of image pixels belonging to different classes. Our experimental results show the
ability of the non-linear, segmentation driven filter of successfully descreening halftone areas while sharpening
small size text contents.
Improper design of color halftone screens may create visually objectionable moire patterns in the final prints due
to the interaction between the halftone screens of the color primaries. The prediction of such interactions from the
screens' bitmaps helps to identify and avoid problematic patterns, reducing the time required to design effective
color halftone screens. In this paper, we detect the moire patterns by examining the spatial frequency spectra of
the superimposed screens. We study different windowing techniques including Hann, Hamming, and Blackman,
to better estimate the moire strength, frequency and orientation. The window-based spectral estimation has
the advantage of reducing the effect of spectral leakage associated with the non-windowed discrete signals. Two
methods are used to verify the detected moire from the bitmaps. First, we analyze scans of the printed halftones,
using the same technique that we applied to the bitmaps. Second, we independently inspect the printed halftones
visually. Our experiments show promising results by detecting the moire patterns from both the bitmap images
as well as the scans of the actual prints verified by visual inspection.
In this paper, we propose new techniques for detecting and quantifying print defects. In our previous work, we
introduced a scanner-based print quality system to characterize directional print defects, such as banding, jitter,
and streaking. We extend our previous print quality work two ways. First, we introduce techniques for detecting
2-D isotropic, mottled print defects such as grain and mottle. Wavelet pre-filtering is used to limit the defect's
size or frequency range. Then we analyze the L* variation in the wavelet-processed images. The methods used
to quantify grain and mottle are similar to ISO/IEC 13660 techniques. The second part of this paper provides
techniques for detecting and quantifying low frequency directional defects, which we call left-to-right and
top-to-bottom L* variation. Since these defects extend less than two cycles across the page, and probably less than
a complete cycle, we fit a 4th-degree polynomial to the defect profile. To measure the strength of the defect,
we use variational analysis of the fitted polynomial. Experimental results on 10 printers and 100 print samples
showed an average correlation for isotropic defects of 0.85 between the proposed measures and experts' visual
evaluation, and 0.97 for low frequency defects.
In this paper we present a unified framework for physical print quality. This framework includes a design for
a testbed, testing methodologies and quality measures of physical print characteristics. An automatic belt-fed
flatbed scanning system is calibrated to acquire L* data for a wide range of flat field imagery. Testing
methodologies based on wavelet pre-processing and spectral/statistical analysis are designed.
We apply the proposed framework to three common printing artifacts: banding, jitter, and streaking. Since
these artifacts are directional, wavelet based approaches are used to extract one artifact at a time and filter
out other artifacts. Banding is characterized as a medium-to-low frequency, vertical periodic variation down
the page. The same definition is applied to the jitter artifact, except that the jitter signal is characterized as
a high-frequency signal above the banding frequency range. However, streaking is characterized as a horizontal
aperiodic variation in the high-to-medium frequency range.
Wavelets at different levels are applied to the input images in different directions to extract each artifact within
specified frequency bands. Following wavelet reconstruction, images are converted into 1-D signals describing
the artifact under concern. Accurate spectral analysis using a DFT with Blackman-Harris windowing technique
is used to extract the power (strength) of periodic signals (banding and jitter). Since streaking is an aperiodic
signal, a statistical measure is used to quantify the streaking strength.
Experiments on 100 print samples scanned at 600 dpi from 10 different printers show high correlation (75%
to 88%) between the ranking of these samples by the proposed metrologies and experts' visual ranking.