Image processing algorithm for characterization of...

Image analysis – Applications – Document or print quality inspection

Reexamination Certificate

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Details

C382S167000, C382S224000, C382S275000, C358S001900, C358S003260, C358S518000

Reexamination Certificate

active

06571000

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of Invention
The invention relates to an image quality analysis system and method that can discern and quantify problems with color non-uniformity.
2. Description of Related Art
It is well known that customer satisfaction can be improved and maintenance costs reduced if problems with copiers and printers can be fixed before they become serious enough to warrant a service call by the customer. While current technology exists to enable printers and copiers to call for service automatically when sensors detect certain operating parameters outside of permissible ranges, there is not a very comprehensive manner of detecting incipient system failure or automatically diagnosing when problems with image quality reach a level where human observers perceive a reduction in quality. This is caused not only by the large number of operating parameters that would need to be tracked, but also because these parameters are strongly coupled to one another. That is, a given parameter at a certain value may or may not be a problem depending on the values of other parameters. While existing systems provide some level of image quality analysis, these systems have been found less than satisfactory as image quality determination is machine dependent and may be inconsistent with perceptions of image quality as judged by human users.
Of particular importance in determining overall image quality is resolving problems with color non-uniformity. However, there are several reasons why color may be non-uniform and mere identification of image quality as it pertains to color uniformity does not resolve identification of the sources of the non-uniformity or provide insight into diagnosis of such problems.
SUMMARY OF THE INVENTION
There is a need for image output devices, such as printers and copiers, to better self-diagnose problems relating to image quality. Applicants have found that to comprehensively and reliably measure the system performance of a printer or copier, the image quality of the output must be measured.
There also is a need for an image quality analysis system that can not only quantify color non-uniformity, but also isolate or characterize the source of the non-uniformity so that one may better diagnose the device and determine a suitable course of action to remedy the non-uniformity.
Systems that can perform image analysis on printed test samples can be used in a variety of ways to provide solutions and value to users of digital printers and copiers, for example as the analysis engine for automatic and/or remote diagnosis of print quality problems, or for monitoring image quality as part of a print quality assurance system. The specific analysis method of this invention can for example be used as an aid in design of halftoning techniques, since it can isolate non-uniformity caused directly by the halftone from that caused by process noise.
One exemplary embodiment of the systems and methods of the invention overcomes such problems by developing powerful diagnosing tools within a digital printer or copier for self-diagnosis and evaluation of image quality. Image quality analysis can be performed to monitor many aspects of the printed output of the printing system. Of particular importance to overall image quality is color non-uniformity.
In this embodiment, the system provides: one or more digital test patterns stored in memory or on disk (or stored in hard copy form) for providing one or more hard copy test images; an input scanner that can scan the hard copy test image to form a digital raster image; and an image quality analysis module that receives information about the position of the digital raster image and produces test results relevant to determination of image quality analysis as perceived by human observers, particularly color non-uniformity. The input scanner and image quality analysis module may form part of the image output device or may be stand-alone components used to test the device. Optionally, a communication module may be provided that is capable of contacting a service department or a more sophisticated diagnostic module if further analysis or service is necessary, depending on the outcome of the image quality analysis. Alternatively, information relating to color non-uniformity may be used by a corrective procedure within the image output device being tested to correct for detected non-uniformity. The image quality analysis and any subsequent corrective procedure should preferably be based on the human visual system (HVS) such that it is possible to determine when differences in certain image quality traits are sufficiently perceived by human observers in order to decide whether corrective action is required.
This invention specifically covers one of the many image quality (IQ) metrics that can be part of an overall image quality (IQ) analysis engine. The specific problem with image quality addressed with this metric is that of a region of a printed (or copied) image, which was intended to have a uniform color, but which shows visible color variations. The color variation can have many different forms, both with respect to the type of color difference and with respect to the spatial nature of the non-uniformities.
A first aspect of the invention thus provides a way of evaluating the absolute image quality (IQ) with respect to uniformity, for example, as part of an IQ assurance inspection system. For this application it is important that the IQ can be evaluated in a manner that is applicable across all printing technologies (electrophotography, lithography, ink-jet, etc.) and that the metric produces values that directly correlate with the human visual impression of the uniformity. As such, comparisons can be made across various product lines with a common IQ value.
A second aspect of the invention uses the results from the IQ analysis as part of a system for machine diagnostics. In this case, images from a printer/copier would be scanned back by a stand-alone scanner or a scanner associated with the printer/copier, and fed into an image analysis module, which would then quantify different types of non-uniformities and use this as a basis for diagnosing machine problems. For this application it is also very important to be able to distinguish between non-uniformities in the different categories, including: (a) amplitude modulated cluster dot halftone patterns; (b) frequency modulated halftone patterns (e.g., stochastic screens); (c) irregular two-dimensional variations from noise; (d) isolated (non-periodic) one-dimensional streaks; (e) periodic, one-dimensional bands; and (f) one- or two-dimensional periodic variations (Moire).
For example, non-uniformities in category (a) would be a result of the normal operation of the printer and not require any corrective action, while excessive non-uniformities in category (c) would be a diagnostic signal that the printer needs service. If separation between (a) and (c) is not made, the color variation caused by halftone screens could dominate the overall signal, and small but important variations caused by process noise may go undetected, resulting in ineffective diagnosis of printer/copier operation.
As far as the type of color variation is concerned, it may be variations purely in lightness (eCIELab L*), or it could be variations that also include hue and chroma. Although the visual perception of such variations strongly depends on the type of color variation, the invention proposed here applies equally well to all of the above-identified types.
Amplitude modulated cluster dot halftone patterns usually have a relatively high spatial frequency (e.g., 141 lines per inch). These patterns are usually not very objectionable to a human observer. This is partly because the frequency is so high that they are not easily visible, and partly because of their regular, periodic nature. On the other hand, frequency modulated halftone patterns at the same level will be visible and highly objectionable by a human observer unless these are of high spatial frequency, because their irregular nature makes the p

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