Hewlett-packard Development Company, L.p.

Hewlett-packard Company

Jeffrey P Lee

Steven J Simske

Patricia D Lopez

Steven L Webb

Hal J Hansen

Julie T Dawe

Martha A Chavez

Eugene W Pakenham

Theodore W Neff

An image-processing system comprising an image-acquisition device configured to generate a representation of a source object, the representation comprising a plurality of pixels, a processor communicatively coupled to the image-acquisition device, and a memory element communicatively coupled to the processor, the memory element comprising logic configured to determine when the source object is skewed in the representation, and logic configured to identify the borders of an orthogonal portion of the representation responsive to the logic configured to determine, wherein the orthogonal portion comprises unaltered pixels that contain information corresponding to the source object. A method for presenting a representation of a source object comprises acquiring a representation of a source object, the representation formed by a plurality of pixels, identifying the vertices of the source object within the representation, determining if the representation is skewed, calculating a skew angle in response to determining that the representation is skewed, and deriving the borders of the largest orthogonal portion of the representation that comprises unaltered pixels corresponding to the source object.

System and method for manipulating a skewed digital image

An improved progress monitor or progress dialog box for a computer system that uncovers or reveals information as the progress bar indicates progress in addition to changing the colors or shades of the progress bar. The information displayed can be the text of a story, the punch line of a joke, or any other information that can inform or entertain the user.

Method and apparatus for improving a progress monitor during a long computer process

Disclosed is a selective document processing system and method. The selective document processing system includes a digital document analyzer configured to determine a number of regions on a digital document and a data type for each of the regions, the data type for each region being one of a number of predefined data types. The system also includes a first user interface to display the analyzed digital document and to allow the user to perform various functions relative to the displayed digital document including selecting desired regions, deleting regions, etc. The system also includes a selection interface activated from the first user interface for identifying at least one of the predefined data types that are displayed on the first user interface and that are further processed in predetermined processing pipelines.

Segmenting a document into regions associated with a data type, and assigning pipelines to process such regions

A user interface method for launching an optimized final scan of a selected region of interest selected from a preview scan of a document. A user may drag the selected region of interest, presented in a preview scan of a document in a scanner window, and drop it on a software application, the desktop, or a writeable folder, which launches an optimized final scan of the selected region of interest. The image data resulting from the optimized final scan automatically resides in the software application, the desktop, or the writeable folder. In selecting a region of interest from the preview scan, scanner software parameters are updated with information about the region of interest which optimize the final scan. The image data from the optimized final scan is then formatted in the format requested and delivered to the software application, the desktop, or the writeable folder.

User interface for initiating the export of an optimized scanned document using drag and drop

Scanned region type sensitivity logic and scanned region clustering/declustering logic allow the manipulation of regions within a scanned image. A scanned region type sensitivity logic allows the manipulation of region type attributes by allowing a user of a scanner product, through the use of a user interface, to adjust the sensitivity of a particular region type in real time, with the results of the adjustment displayed back to the user through the user interface. A scanned region clustering/declustering logic allows a user of a scanner product, through the use of a user interface, to manipulate the grouping of regions displayed to the user in real time. Both of these forms of scanning logic are predicated on the underlying use of a document analysis technology that stores probabilities (&ldquo;p-values&rdquo;) or other relative statistics on all plausible region types as part of the definition of the regions.

System and method for manipulating regions in a scanned image

A user interface for scanner software that allows a variable resolution preview scan of a document to be presented to the user in a preview box within a scanner software window. The user clicks on a point within the preview scan, and the classification of the image immediately around the click point is determined. A selection marker is automatically drawn around the selected image, and all portions of the preview scan outside the selection marker are grayed out. Based on the classification, adjustments are made automatically, and windows having control tools for adjusting various aspects of the selected image are automatically enabled or disabled. Once the desired area is properly selected and any adjustments have been made, the user can drag and drop the selected image with a mouse onto the desktop, a folder, or an open application to launch an optimized final scan of the selected image.

Click and select user interface for document scanning

A method of filtering images with a filter that is dependent on image type. For binary images, a fixed Laplacian filter is used for all pixels. For non-binary images, an automatic level-sensitive Laplacian filter is used. For non-binary images, Laplacian filter coefficients and normalization divisors are made a function of intensity on a pixel by pixel basis. Pixels indicating a high intensity may be greatly changed by neighboring pixels. Pixels indicating a low intensity receive relatively little or no filtering. In a specific example embodiment, the intensity range is divided to bands, with a different filter for each band. The resulting images are visually sharpened (edge enhanced) with very little impact in darker areas of the image.

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Greeley, CO, United States of America

Jeffrey P Lee