Intellectual Ventures Fund 83 LLC

Eastman-kodak Company

Kodak Alaris Inc.

Jeffrey Clarence Snyder

Elena A Fedorovskaya

Sharon Lynn Chu Yew Yee

Andrew Frederick Kurtz

Andrew Charles Gallagher

Edward B Gindele

Kevin Edward Spaulding

James E Adams, Jr

Raymond William Ptucha

William Vernon Fintel

Navid Serrano

Gail Shepter

Joel Sherwood Lawther

A method of producing barcode locations within a document comprising providing an original digital image of the document; using a processor for producing a normalized image from the original digital image; producing a gradient image from the normalized image; producing a plurality of bounding boxes from the gradient image; and producing bounding box test results by testing each bounding box for the presence of a barcode; and producing barcode locations within the document from the bounding box test results.

Determining barcode locations in documents

A method for presenting digital images having a high interest level to a particular person selected from a set of candidate digital images. The candidate digital image are analyzed to designate one or more image elements, and familiarity levels are determined of the designated image elements to the particular person. For each candidate digital image, an associated interest level to the particular person is determined responsive to the determined familiarity levels. One or more of the candidate digital images are selected based on the determined interest levels and are presented to the particular person.

Method for presenting high-interest-level images

A method for increasing the interest level of a digital image to a particular person based on an interest level function that determines an interest level of a particular digital image to the particular person responsive to familiarity levels of image elements in the particular digital image. The initial digital image includes one or more image elements having associated initial familiarity levels, the initial digital image having an initial interest level as characterized by the interest level function responsive to the initial familiarity levels. The set of image elements are modified, thereby providing a modified digital image having an increased interest level to the particular person as characterized by the interest level function responsive to modified familiarity levels associated with the modified image elements. The modified digital image is then displayed to the particular person.

Modifying digital images to increase interest level

A method for determining an interest level of a digital image to a particular person. The digital image, or metadata associated with the digital image, is analyzed to designate one or more image elements in the digital image. Familiarity levels of the designated image elements to the particular person are determined. The interest level of the digital image to the particular person is then determined responsive to the determined familiarity levels. In some embodiments the image elements include persons and scene contexts, where digital images containing more familiar persons and less familiar scene contexts correspond to higher interest levels.

Determining an interest level for an image

A system comprising an image display; a digital camera positioned to capture images of persons viewing the image display; and a memory system storing instructions configured to cause a data processing system to implement a method for presenting digital images having a high interest level to a particular person selected from a set of candidate digital images. The method includes using the digital camera to capture an image including a particular person positioned to view the image display. The candidate digital images are analyzed to designate one or more image elements, and familiarity levels of the designated image elements to the particular person are determined. For each candidate digital image, an associated interest level to the particular person is determined responsive to the determined familiarity levels. One or more of the candidate digital images are selected based on the determined interest levels and are presented to the particular person.

System for presenting high-interest-level images

A method of processing an image to form an image pyramid having multiple image levels includes receiving a base level image comprising pixel values at pixel locations arranged in rows and columns; determining sample locations for a next level image in the pyramid such that the sample locations are arranged in a regular pattern and the sample locations exceed the range of the pixel locations of the base level image; determining the pixel values of the next level image by interpolating the pixel values of the base level image using an interpolation filter at the sample locations; and treating the next level image as the base level image and repeating steps of determining sample locations and pixel values until a predetermined number of pyramid image levels are generated, or until a predetermined condition is met.

Method of processing an image to form an image pyramid

In an image enhancement method, a regular enhancement function and an aggressiveness parameter are computed using characteristics of a digital image. A first, relatively slow enhancement algorithm is applied to the digital image using the regular enhancement function, when an aggressiveness parameter is in a predetermined high range. A second, relatively fast enhancement algorithm is applied to the digital image using the regular enhancement function, when an aggressiveness parameter is in a predetermined low range. A modified enhancement function is calculated using characteristics of the digital image and is used with a second, relatively fast enhancement algorithm, when the aggressiveness parameter is in a predetermined medium range.

Selection of alternative image processing operations to maintain high image quality

A method for estimating a noise characteristic value for a plurality of digital images that are affected by a common noise source includes receiving a plurality of source digital images that are affected by a common noise source, each source digital image including a plurality of pixels; calculating a total number of pixels included in the source digital images; and receiving a predetermined target number of noise estimates to be calculated for the source digital images. The method also includes using the total number of pixels and the predetermined target number of noise estimates to calculate one or more pixel sampling parameters for the source digital images; using the source digital images and the one or more pixel sampling parameters to calculate a predetermined number of noise estimates; and using the noise estimates to calculate a noise characteristic value for the source digital images.

Growing community of inventors

Fairport, NY, United States of America

Jeffrey Clarence Snyder