Facsimile and static presentation processing – Static presentation processing – Attribute control
Reexamination Certificate
1998-08-10
2001-04-24
Rogers, Scott (Department: 2624)
Facsimile and static presentation processing
Static presentation processing
Attribute control
C358S451000, C358S463000, C358S465000, C382S169000, C382S172000, C382S275000
Reexamination Certificate
active
06222642
ABSTRACT:
FIELD OF THE PRESENT INVENTION
The present invention is directed to the imaging arts. It finds particular application to a system or method of determining and eliminating background pixels from a scanned image during reproduction of the image and will be described with particular reference thereto. Of course, it is to be appreciated that the invention will also find application to other image reproduction processes and devices such as displaying or printing a digital image or copying an image.
BACKGROUND OF THE PRESENT INVENTION
In a conventional reproduction machine, a document (image) is scanned so that light reflected from the document causes a latent image of electrical charges to form on a photoreceptor. This latent image is then developed with toner, and the toner is transferred to a recording medium to produce a copy of the scanned document. These systems are commonly referred to as light-lens or non-digital copying systems.
The quality of a light-lens reproduction machine is a function of how well the copy matches the original. As is well know, various factors can impact this quality. For example, the scanning station can impact the quality if the optical path of the scanning station is not properly aligned. Also, the development station can impact the quality if a photoreceptor is not properly cleaned.
With the advent of digital reproduction machines, the above copy process for making a copy has changed. In a digital process, a document or image is scanned by a digital scanner which converts the light reflected from the document into electrical charges representing the light intensity from predetermined areas (pixels) of the document. These charges, after suitable processing, are converted into image signals or pixels of image data to be used by the digital reproduction machine to recreate the scanned image.
The pixels of image data are processed by an image processing system which converts the pixels of image data into signals which can be utilized by a printing device to recreate the scanned image. This printing device may be either a xerographic printer, ink jet printer, thermal printer, or any other type of printing device which is capable of converting digital data into a mark on a recording medium.
As with the light-lens systems, the quality of a reproduction machine is still a function of how well the copy matches the original. However, in this digital environment, other factors can now contribute to or impact the quality of the reproduced image. For example, the scanner can impact the quality if the scanner is not properly calibrated. Also, the output (printing) device can impact the quality if a printhead is clogged or a photoreceptor is not properly cleaned. But, the aspect of the digital system which can have the greatest impact is the digital (image) processing of the image data because a digital machine must convert light to a digital signal and then convert the digital signal to a mark on a recording medium. In other words, the image processing system provides the transfer function between the light reflected from the document to the mark on the recording medium.
Quality can be measured in many different ways. One way is to look at the characteristics of the reproduced image. An example of such a characteristic for determining the quality of the reproduced image is the contrast of the image. The contrast of an imaged (copied) document is the most commonly used characteristic for measuring quality since contrast provides a good overall assessment of the image's quality.
In a digital reproduction machine, the image processing system can greatly impact the contrast of the image. Thus, to assure high quality at the output printing device, it is desirable to know the contrast of the image being scanned prior to the image processing stage because, with this knowledge, the image processing system can process the image data so that the reproduced image has the proper contrast. One way of obtaining this contrast information prior to digital image processing is for the digital reproduction machine to generate a grey level histogram, which gives an easy to read measure of the image contrast. The image or grey level histogram describes the statistical distribution of grey levels of an image in terms of the number of pixels at each grey level. In other words, the number of pixels within an image that are associated with a certain grey level.
A histogram can be represented graphically with intensity on the horizontal axis from 0 to 255, if an eight-bit per pixel sampling resolution is utilized, and the number of pixels on the vertical axis. Using this graphical representation, a histogram can illustrate whether an image is basically dark or light and high or low contrast. It is important to know that when an image is represented by histogram, all spatial information is lost. The histogram specifies the number of pixels of each grey level but gives no indication where these pixels are located in the image. In other words, very different images may have very similar histograms.
Conventionally, when creating a histogram of the scanned image, a digital reproduction system samples a document, collects intensity data from the document, and uses this information to determine the document's background value. In such conventional systems, the computed background value of the document represents the average intensity of the document.
While this conventional approach produces reasonable results for many documents, the conventional approach is sensitive to the image's composition and is also insensitive to intensity variations within a document's background. As the make up of the document shifts from predominantly background to text and graphics, the value reported by an averaging scheme will change proportionally. If the magnitude of this change is significant, the area corresponding to the change will manifest itself in the output copy of the scanned document as a thinning or loss of fine lines and characters.
Therefore, it is desirable to utilize a system and method for generating histogram data which is insensitive to the image composition in the sampled area and is sensitive to intensity variations within the document's background. When utilizing such a system or method, the background value and black threshold value of the document will not change as the sample region shifts in character from predominantly background to text and graphics, and thus, the output copy from the printing device will not realize a thinning or loss of fine lines and characters.
SUMMARY OF THE PRESENT INVENTION
In one aspect of the present invention, a system for eliminating background grey values from an image is provided. A scanner scans and converts the image into digital signals representing grey values of the image. A histogram generator generates a histogram of frequencies of the grey values of the image and determines a background peak value representing a background color having a peak frequency in the histogram. A thresholding circuit generates a background threshold value based on a difference between a background peak value and a scaled offset. The scaled offset includes a scaling factor which is selectable. The background threshold value is a cut-off value for eliminating background grey values from reproduction of the image.
In another aspect of the present invention, a method of suppressing a background image from a document being reproduced is provided. The document is formed of a plurality of video pixels each having a grey value. A histogram is generated representing a frequency of occurrence of the grey values based on the plurality of video pixels. A background peak grey value is determined from the histogram where the background peak grey value is a grey value having a greatest frequency of occurrence in the histogram. The background peak grey value is a basis for identifying a range of grey values representing the background image. The range of grey values representing the background image is expanded by scaling the background peak grey value. The docum
Farrell Barbara L.
Shiau Jeng-Nan
Fay Sharpe Fagan Minnich & McKee LLP
Rogers Scott
Xerox Corporation
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