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Title: Method for non-referential defect characterization using fractal encoding and active contours

Abstract

A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

Inventors:
 [1];  [2]
  1. Knoxville, TN
  2. Lubbock, TX
Issue Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
909404
Patent Number(s):
7218772
Application Number:
10/166,296
Assignee:
Ut-Battelle LLC (Oak Ridge, TN)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION

Citation Formats

Gleason, Shaun S, and Sari-Sarraf, Hamed. Method for non-referential defect characterization using fractal encoding and active contours. United States: N. p., 2007. Web.
Gleason, Shaun S, & Sari-Sarraf, Hamed. Method for non-referential defect characterization using fractal encoding and active contours. United States.
Gleason, Shaun S, and Sari-Sarraf, Hamed. Tue . "Method for non-referential defect characterization using fractal encoding and active contours". United States. https://www.osti.gov/servlets/purl/909404.
@article{osti_909404,
title = {Method for non-referential defect characterization using fractal encoding and active contours},
author = {Gleason, Shaun S and Sari-Sarraf, Hamed},
abstractNote = {A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2007},
month = {5}
}

Works referenced in this record:

Multiple same-sized block mapping for recursive fractal image coding
journal, February 2002


Front-end data reduction in computer-aided diagnosis of mammograms: a pilot study
conference, May 1999


Nonlinear filter derived from topological image features
conference, September 1990


Detection of semiconductor defects using a novel fractal encoding algorithm
conference, July 2002

  • Gleason, Shaun S.; Ferrell, Regina K.; Karnowski, Thomas P.
  • Design, Process Integration, and Characterization for Microelectronics, SPIE Proceedings
  • https://doi.org/10.1117/12.475642

Higher accuracy and throughput in computer-aided screening of mammographic microcalcifications
conference, January 1997