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Title: System and method for automated object detection in an image

Abstract

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

Inventors:
; ; ; ;
Issue Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1222628
Patent Number(s):
9152888
Application Number:
14/026,730
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Sep 13
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Kenyon, Garrett T., Brumby, Steven P., George, John S., Paiton, Dylan M., and Schultz, Peter F. System and method for automated object detection in an image. United States: N. p., 2015. Web.
Kenyon, Garrett T., Brumby, Steven P., George, John S., Paiton, Dylan M., & Schultz, Peter F. System and method for automated object detection in an image. United States.
Kenyon, Garrett T., Brumby, Steven P., George, John S., Paiton, Dylan M., and Schultz, Peter F. Tue . "System and method for automated object detection in an image". United States. https://www.osti.gov/servlets/purl/1222628.
@article{osti_1222628,
title = {System and method for automated object detection in an image},
author = {Kenyon, Garrett T. and Brumby, Steven P. and George, John S. and Paiton, Dylan M. and Schultz, Peter F.},
abstractNote = {A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {10}
}

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Works referenced in this record:

Contour statistics in natural images: Grouping across occlusions
journal, January 2009


Alternatives to a table of criterion values in signal detection theory
journal, May 1986


Support-vector networks
journal, September 1995


ART neural networks for remote sensing: vegetation classification from Landsat TM and terrain data
journal, March 1997


Object recognition from local scale-invariant features
conference, January 1999


Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
journal, February 2003


Classification of transient signals using sparse representations over adaptive dictionaries
conference, June 2011


Receptive fields and functional architecture of monkey striate cortex
journal, March 1968


Task-Driven Dictionary Learning
journal, April 2012


Sparse Representation for Color Image Restoration
journal, January 2008


A model of saliency-based visual attention for rapid scene analysis
journal, January 1998


Simplified neuron model as a principal component analyzer
journal, November 1982


Emergence of simple-cell receptive field properties by learning a sparse code for natural images
journal, June 1996


Trailblazing with Roadrunner
journal, July 2009


Spatial frequency selectivity of cells in macaque visual cortex
journal, January 1982


The orientation and direction selectivity of cells in macaque visual cortex
journal, January 1982


Hierarchical models of object recognition in cortex
journal, November 1999


Matching pursuits with time-frequency dictionaries
journal, January 1993


Large-scale functional models of visual cortex for remote sensing
conference, October 2009


A feedforward architecture accounts for rapid categorization
journal, April 2007


Robust Object Recognition with Cortex-Like Mechanisms
journal, March 2007