Pattern recognition filters for digital images

Image analysis – Pattern recognition

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C244S158100, C382S276000, C382S294000

Reexamination Certificate

active

08041118

ABSTRACT:
In an exemplary embodiment, a pattern is recognized from digitized images. A first image metric is computed from a first digitized image and a second image metric is computed from a second digitized image. A composite image metric is computed as a function of the first image metric and the second image metric, and a pattern is identified by comparing the composite image metric against a reference image metric. The function may be a simple average or a weighted average. The image metric may include a separation distance between features, or a measured area of a feature, or a central angle between two arcs joining a feature to two other features, or an area of a polygon whose vertices are defined by features, or a second moment of a polygon whose vertices are defined by features. The images may include without limitation images of friction ridges, irises, or stars.

REFERENCES:
patent: 5223702 (1993-06-01), Conley
patent: 5291560 (1994-03-01), Daugman
patent: 5706416 (1998-01-01), Mann et al.
patent: 6102338 (2000-08-01), Yoshikawa et al.
patent: 6227496 (2001-05-01), Yoshikawa et al.
patent: 6236939 (2001-05-01), Wu et al.
patent: 6241288 (2001-06-01), Bergenek et al.
patent: 6266216 (2001-07-01), Hikami et al.
patent: 6470270 (2002-10-01), Needelman et al.
patent: 6512979 (2003-01-01), Needelman et al.
patent: 6522768 (2003-02-01), Dekhil et al.
patent: 6523786 (2003-02-01), Yoshikawa et al.
patent: 6766227 (2004-07-01), Needelman et al.
patent: 6785427 (2004-08-01), Zhou
patent: 7038710 (2006-05-01), Caviedes
patent: 7136752 (2006-11-01), Needelman et al.
patent: 7260456 (2007-08-01), Fowell et al.
patent: 7650016 (2010-01-01), Gold, Jr.
patent: 7764844 (2010-07-01), Bouk et al.
patent: 2008/0069445 (2008-03-01), Weber
patent: 2008/0199077 (2008-08-01), Fowell
Polle, B., et al., “Autonomous On-Board Navigation for Interplanetary Missions (AAS 03-023),” 26th Annual AAS Guidance and Control Conference, Feb. 5-9, 2003, pp. 277-293, American Astronautical Society, San Diego, California, USA.
Jeffrey N. Blanton, “A New Collapsing Technique for Star Identification Using Sensors with Nonsimultaneous Acquisition Times (ADA096242),” Oct. 1980, 13 pages, Navel Surface Weapons Center, Dahlgren, Virginia, USA.
Jeffrey N. Blanton, “The Application of a State Transition Matrix Solution for the Rotational Motion of a Satellite to Star Identification (AAS 81-171),” Aug. 1981, 12 pages, vol. 46, Part II, Advances in the Astronautical Sciences, Astrodynamics Conference, North Lake Tahoe, Nevada, USA.
Meng Na and Peifa Jia, “A survey of all-sky autonomous star identification algorithms,” Systems and Control in Aerospace and Astronautics, Jan. 2006, pp. 896-901.
Kara M. Huffman, “Designing Star Trackers to Meet Micro-satellite Requirements,” May 26, 2006, 187 pages, Master of Science in Aeronautics and Astronautics at the Massachusetts Institute of Technology.
Jean Claude Kosik, “Star Pattern Identification Aboard an Inertially Stabilized Spacecraft,” Centre National d'Etudes Spatiales, pp. 230, vol. 14, No. 2, Toulouse, France.
James R. Wertz, “Spacecraft Attitude Determination and Control,” Copyright © 1978, pp. 424-428 and 259-266, Kluwer Academic Publishers, Dordrecht, The Netherlands.
Keith Price, “Annotated Computer Vision Bibliography: Table of Contents,” http://iris.usc.edu/Vision-Notes/bibliography/contents.html, last update: Jun. 25, 2008, 1 page.
Jon Holtzman, “Basic Principles and Properties,” http://ganymede.nmsu.edu/holtz/a535/ay535notes
ode48.html, Dec. 7, 2007, 2 pages.
Jon Holtzman, “CCDs,” http://ganymede.nmsu.edu/holtz/a535/ay535notes
ode49.html, Dec. 7, 2007, 1 page.
John Biretta and Michael S. Wiggs, “WFPC2 Data Reduction / Technical Issues,” http://www.stsci.edu/ftp/science/hdfsouth/reduc—wfpc2.html, last updated on Nov. 24, 1998, 5 pages.
A. S. Fruchter and R. N. Hook, “Linear Reconstruction of the Hubble Deep Field,” http://www-int.stsci.edu/˜fruchter/dither/drizzle.html, Sep. 15, 1996, 7 pages.
Zomet et al., Robust Super-Resolution, School of Computer Science and Engineering, The Hebrew University of Jerusalem, 2001 IEEE.
Kuehl et al., Micro-Tech.-Sensor for Attitude and Orbit Determination, AAS 03-001, 26th AAS G&C Conference, Feb. 2003.
Bae et al., Precision Attitude Determination (PAD), Geoscience Laser Altimeter System (GLAS)—Algorithm Theoretical Basis Document-Version 2.2, Center for Space Research, The University of Texas at Austin, Oct. 2002.
Airey et al., Seeing Through Dust—Tracking Stars from within a Cometary Dust Cloud, AAS 03-022, 26th AAS G&C Conference, Feb. 2003.
Whirlpool Galaxy Image, http://www.whirlpoolgalaxy.com/image—stacking.html, Astrophotography of Jay Potts, viewed May 24, 2011.
Image Stacker Help, http://www.tawbaware.com/is—help/imgstack—help.htm, viewed May 24, 2011.
Rao et al., Incremental-Angle and Angular Velocity Estimation Using a Star Sensor, Journal of Guidance, Control, and Dynamics, vol. 25-No. 3, May-Jun. 2002.
Borman et al., Spatial Resolution Enhancement of Low-Resolution Image Sequences—A Comprehensive Review with Directions for Future Research, Laboratory for Image and Signal Analysis (LISA), University of Notre Dame, Indiana, Jul. 8, 1998.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Pattern recognition filters for digital images does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Pattern recognition filters for digital images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Pattern recognition filters for digital images will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4281915

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.