Hewlett-packard Development Company, L.p.

Hewlett-packard Company

Charles Chi Jia

Laura Zhou

Anne-Marie Woodson

Cindy Y Sansom-Wai

Daniel R Tretter

Jian Fan

Jinman Kang

Guo Li

Yifeng Wu

David M Berfanger

Laurel Lasslo

Daniel Wee

Gary Mark Nobel

Melissa Lee Monty

Kevin A Merrill

Cindy Sansom

Howard Merrill

Lynn M Eades

Curtis Young

Christopher Arrioia

Michael Stephen Rose

Wade Patrick Mears

William Edward Stewart

Adelaida Escobedo

James Xin-Ping Zheng

Jackie Shi Chung Fung

Stanley McDaniel

According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions executable by the processor to detect edges of a scanned object image. The instructions may also cause the processor to determine, based on the detected edges, that a feed skew has occurred on the scanned object image. In addition, based on a determination that the feed skew has occurred, the instructions may cause the processor to identify curved edges of the scanned object image, de-curve the identified curved edges through horizontal scanline scaling of the scanned object image to form a de-curved image, and produce a corrected image through vertical scanline scaling of the de-curved image.

Correction of feed skewed images

A technique includes acquiring data representing a first image produced by electronically scanning a page against a background. The first image contains a non-uniform background content due at least in part to a variation introduced by the background being non-uniform. The technique includes extracting an image of the page from the first image, wherein the extraction includes characterizing the background content of the first image; identifying candidate pixels associated with the page based at least in part on the characterized background content; and based at least in part on the identified candidate pixels and a model for a boundary of the page, determining the boundary of the page.

Extracting a document page image from a electronically scanned image having a non-uniform background content

Recognizing a command may include monitoring a tangible reference with a depth sensor, maintaining a virtual reference approximately on calibrated three dimensional coordinates of the tangible reference, maintaining a touch space adjacent the virtual reference, and recognizing a command when a predetermined object enters the touch space.

Recognizing commands with a depth sensor

A method for implementing gesture based human interfaces includes segmenting data generated by an IR camera of an active area and detecting objects in an active area. The objects are distinguished as either island objects or peninsula objects and a human hand is identified from among the peninsula objects. The motion of the human hand is tracked as a function of time and a gesture made by the human hand is recognized.

Gesture based human interfaces

A method of image processing is provided, the method including acquiring a digital image having a three-dimensional shadow, determining a boundary of the three-dimensional shadow, and lightening the three-dimensional shadow within the boundary.

Method and apparatus for three-dimensional shadow lightening

A scanning device of one embodiment of the invention is disclosed that includes a scanning mechanism and a removable storage media mechanism disposed within a housing of the scanning device. The scanning mechanism is to scan image data from scannable media. The removable storage media mechanism is receptive to a removable storage medium on which the image data scanned from the scannable media is stored.

Scanning to storage medium using scanning device

A system and method for removing optical iridescent artifacts in an image includes scanning an article having a transparent and reflective surface to create the image, identifying potential optical iridescent artifacts in the image resulting from the scan using a search pattern on the image of the article, confirming through a color analysis operation that the potential optical iridescent artifacts discovered along the search pattern are optical iridescent artifacts and not printed on the article and removing the confirmed iridescent artifacts from the image.

Method and apparatus for automatic removal of optical artifacts in scanning

A method of processing a scanned negative image produced by scanning a negative film includes creating a baseline positive image from the scanned negative image, analyzing at least one image characteristic of the baseline positive image, determining a film type of the negative film based on the at least one image characteristic, and producing a positive image from the scanned negative image based on the film type, including applying film-specific color inversion to the scanned negative image.

System and method of processing scanned negative image

An image processing apparatus and method includes a sub-sampler decompression unit that takes an inverse transformation to rebuild 411 sub sampled luminance/chrominance color space components which are than transformed into full resolution luminance/chrominance color space pixel data. The luminance/chrominance color space pixel data is then separated into individual luminosity and chromaticity components which are scaled. A scaling unit responsive to the sub-sampler decompression unit applies different processing algorithms to the various ones of the luminance and chrominance components to scale the main luminosity component utilizing a spacial algorithm while simultaneously scaling the minor chromaticity components utilizing a perceptual algorithm. The scaled full resolution luminance and chrominance color space components are then converted into RGB color space for display purposes.

Image processing decompression apparatus and method of using same different scaling algorithms simultaneously

An image processing apparatus and method for analyzing a digital image and automatically generating a visually attractive frame for the image. A data set for the image is analyzed, preferably in color space, to determine one or more image components representing dominant colors in the image. The components are characterized individually, and then these individual component characterizations are used to characterize the image overall. Based on the overall image characteristics, the framing scheme parameters are determined and used in turn to generate the attributes of a visually attractive frame for the image. A data set for the framed image is then generated, which may be sent to an imaging device for display or printing, or simply stored as a new data set for later use. The user has the ability to modify the rules that determine the framing scheme parameters so as to adjust the framed image if desired.

Automatic generation of frames for digital images

Methods are provided for use with a computing device and an image scanning device. One method includes performing a scan to produce a preview scanned image, selecting a portion of the preview scanned image for final scanning, and scanning the selected portion of the preview scanned image to produce a final scanned image. Performing the scan to produce the preview scanned image may include performing an autocrop process and a deskew process before displaying the preview scanned image to the user. Once the preview scanned image is displayed, then the user may decide to selectively rotate the preview scanned image, for example, about an anchor point that was used in the deskew process. The user may also select a portion of interest within the image. Once the user is satisfied with the user selected rotation, if any, and the user selected portion of interest, then a final scan will be performed. As part of the final scan process, the method includes calculating an effective portion of the preview scanned image. The effective portion encompasses the selected portion of the preview scanned image. This effective portion or area of the scanner bed is then scanned at the final scan resolution. The resulting scanned effective portion image is then rotated based on the angular parameters associated with the deskew and user selected rotation. Once rotated, the scanned effective portion image is then cropped to match the user selected portion of interest. The resulting portion of interest can then be displayed and stored.

Methods for scanning and processing selected portions of an image

A method of processing a color digital image file provides a 'metallic,' or a 'sepia,' or an &#x201c;antiqued&#x201d; image file. The resulting image files may be viewed, for example, on a computer monitor, or may be printed out in hard copy form using a black-and-white or color printer. A color photocopy machine which has a digital image output may be used to produce the original image file, and such a color photocopier (if it will accept digital image files), may also be used to produce the output hard copy printouts of processed image files. Thus, such a digital photocopier may be configured internally to also process image files, and may be employed to selectively process images copied on the machine into the user's choice of a metallic, a sepia, or an antiqued image on the output hardcopy of the color photocopier.

Digital image processing

Various systems and methods are disclosed to achieve remote processing of items in a client with limited processing capacity. Specifically, a client receives an element that it is unable to render or otherwise process to present to the user due to its limited processing capacity. The client transmits the element to a server that includes various processing modules that allow the server to process the element or otherwise perform the task that was beyond the client capability. The server thus processes the element, thereby converting it into a form that is recognizable by the client. The processed element is then sent back to the client where it is depicted or otherwise executed in the client.

System and method for distributed processing of non-processable elements of a document to be rendered on a client

A method for automatic removal of vertical streaks involves a comparison between image data for a pixel and its neighbor pixels to determine whether the pixel is non-homogenous. In a preferred method, the comparison employs an adaptive threshold against which a difference between the pixel and its neighbor pixels is compared, with the adaptive threshold taking into account accumulative information pertaining to pixels generated by a common optical sensor element. A preferred method also includes the step of considering locations of non-homogenous pixels in the image to determine whether the image data associated with the non-homogenous pixels needs to be changed or modified. A preferred method also includes the step of associating the non-homogenous pixels with different image data.

Growing community of inventors

San Diego, CA, United States of America

Charles Chi Jia