Image analysis – Pattern recognition – Classification
Reexamination Certificate
1998-09-23
2002-06-25
Johns, Andrew W. (Department: 2621)
Image analysis
Pattern recognition
Classification
C382S173000
Reexamination Certificate
active
06411735
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to the document processing system art. It finds particular application in conjunction with image segmentation, and more particularly, a method and apparatus for distinguishing between noisy continuous tone document types and other document types identified by measures and techniques that have undesirable positive responses to video representing noisy continuous tone images, in order to maintain reliable image segmentation. However, it should be appreciated that the present invention may also find application in conjunction with other types of digital imaging systems and applications that discern how an image was rendered.
Document processing systems often need to take an image representation with a low level of organizational structure, such as a simple bit or byte per pixel rectangular video map, and infer structure to guide further processing or analysis of the image. For example, in a reprographic system a document is optically scanned and the reflectance of each pixel is converted to a multi-bit (e.g. 8-bit) digital value, forming a matrix of integers representing the original document.
Various image processing is then performed to enhance the image and convert it to a different resolution and form which can be rendered by a particular marking technology, such as a bi-level Xerographic printer. The purpose of the processing is to produce an output copy which appears to the human eye to be equal to or in some sense better than the original. Unfortunately, the appropriate image processing is different for different types of input documents, typical broad classes being text, continuous tone, and halftones of various techniques and frequencies.
Furthermore, many user originals contain more than one document type in different areas of the page, for example a magazine article with inset halftoned photographs, or text embedded in a tinted background. This explains the need to classify each document pixel, so that appropriate processing can be performed. In other applications, the pixel classification can be communicated to a subsequent process that analyzes the pixel level classification map further.
Algorithms for classifying image pixels according to document type (e.g. text, contone, halftone) make their decision based on image context in the vicinity of the pixel being classified. In the case of a halftone document type, the absolute value of the sum of the laplacians in a small area surrounding the pixel being classified (abbreviated Sij), and the halftone peak count within a context surrounding the pixel being classified, are typically used to detect halftones. However, continuous tone documents which are very noisy, or video from very noisy scanners, can fool such algorithms if enough false video peaks are detected and Sij is large enough. This results in the contone image appearing splotchy on the output document. The splotchy appearance is due to the inappropriate switching between rendering schemes based on varying peak density and Sij.
In the past these defects were not visible because the use of hysteresis or other state-based methods, along with rectangular segmentation blocks over which statistics were accumulated suppressed such errors, as did rendering TRCs designed to hide shortfalls not only in segmentation, but also in other parts of the system as well, such as the scanner.
However, recent advances in scanner technology and image segmentation, driven by the desire to more faithfully reproduce the original image, have eliminated the state-based methods and the use of rectangular segmentation blocks. TRCs no longer saturate in the dark and light areas to hide flaws in the system, but are designed to faithfully render the original document at all densities. The new segmentation schemes avoid generation of rectangular artifacts by classifying each pixel independently, precluding the possibility of neighborhood classification statistics overriding a given pixel's erroneous classification, thereby hiding errors. Thus, without state-based methods or the use of blocks over which classification statistics can be gathered to suppress errors when aberrations in the classification occur, pixels are incorrectly classified and subsequently rendered.
Accordingly, it has been considered desirable to develop a new and improved method and apparatus for distinguishing between noisy continuous tone document types and other document types identified by measures and techniques that have undesirable positive responses to video representing noisy continuous tone images, in order to maintain reliable image segmentation, that meets the above-stated needs and overcomes the foregoing difficulties and others while providing better and more advantageous results.
SUMMARY OF THE INVENTION
The present invention consists of adding a range of video requirement to a document type classification process in order to distinguish between many small video variations associated with a noisy continuous tone document type, and a smaller number of large variations associated with other document types such as halftone or text.
In accordance with one aspect of the present invention, a method for classifying a pixel of image data as one of a plurality of image types is disclosed. The method includes the steps of determining a first image characteristic value for the pixel being classified, determining a provisional classification for the pixel being classified, and assigning an image type classification to the pixel being classified based on the first image characteristic value and the provisional classification.
In accordance with another aspect of the present invention, a system for classifying a pixel of image data according to one of a plurality of image types is disclosed. The system includes a first mechanism for determining a first image characteristic value of the pixel being classified, a second mechanism for determining a provisional classification of the pixel being classified, a classifier for assigning an image type classification to the pixel being classified based on the first image characteristic value and the provisional classification, and a processor for image processing the pixel based on the image type classification of the pixel.
One advantage of the present invention is the provision of a method and apparatus for distinguishing between noisy continuous tone document types and other document types.
Another advantage of the present invention is the provision of a method and apparatus for providing reliable image segmentation.
Yet another advantage of the present invention is the provision of a method and apparatus that correctly renders noisy continuous tone document types.
A further advantage of the present invention is the provision of a method and apparatus that correctly identifies subsequent processing, utilization, or identification of higher level image semantics.
Still further advantages of the present invention will become apparent to those of ordinary skill in the art upon reading and understanding the following detailed description of the preferred embodiment.
REFERENCES:
patent: 4194221 (1980-03-01), Stoffel
patent: 5293430 (1994-03-01), Shiau et al.
patent: 5748776 (1998-05-01), Yoshida
patent: 6185328 (2001-02-01), Shiau
Clark Raymond J.
Schweid Stuart A.
Williams Leon C.
Azarian Seyed
Fay Sharpe Fagan Minnich & McKee LLP
Johns Andrew W.
Xerox Corporation
LandOfFree
Method and apparatus for distinguishing between noisy... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method and apparatus for distinguishing between noisy..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and apparatus for distinguishing between noisy... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2931794