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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
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN
Sponsoring Org.:
USDOE
OSTI Identifier:
909404
Patent Number(s):
7,218,772
Application Number:
10/166,296
Assignee:
Ut-Battelle LLC (Oak Ridge, TN) ORO
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. doi:. 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 = {Tue May 15 00:00:00 EDT 2007},
month = {Tue May 15 00:00:00 EDT 2007}
}

Patent:

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  • A method used preferably with LZSS-based compression methods for compressing a stream of digital data. The method uses a run-length encoding scheme especially suited for data strings of identical data bytes having large run-lengths, such as data representing scanned images. The method reads an input data stream to determine the length of the data strings. Longer data strings are then encoded in one of two ways depending on the length of the string. For data strings having run-lengths less than 18 bytes, a cleared offset and the actual run-length are written to an output buffer and then a run bytemore » is written to the output buffer. For data strings of 18 bytes or longer, a set offset and an encoded run-length are written to the output buffer and then a run byte is written to the output buffer. The encoded run-length is written in two parts obtained by dividing the run length by a factor of 255. The first of two parts of the encoded run-length is the quotient; the second part is the remainder. Data bytes that are not part of data strings of sufficient length are written directly to the output buffer.« less
  • A method used preferably with LZSS-based compression methods for compressing a stream of digital data is disclosed. The method uses a run-length encoding scheme especially suited for data strings of identical data bytes having large run-lengths, such as data representing scanned images. The method reads an input data stream to determine the length of the data strings. Longer data strings are then encoded in one of two ways depending on the length of the string. For data strings having run-lengths less than 18 bytes, a cleared offset and the actual run-length are written to an output buffer and then amore » run byte is written to the output buffer. For data strings of 18 bytes or longer, a set offset and an encoded run-length are written to the output buffer and then a run byte is written to the output buffer. The encoded run-length is written in two parts obtained by dividing the run length by a factor of 255. The first of two parts of the encoded run-length is the quotient; the second part is the remainder. Data bytes that are not part of data strings of sufficient length are written directly to the output buffer. 3 figs.« less
  • A method used preferably with LZSS-based compression methods for compressing a stream of digital data. The method uses a run-length encoding scheme especially suited for data strings of identical data bytes having large run-lengths, such as data representing scanned images. The method reads an input data stream to determine the length of the data strings. Longer data strings are then encoded in one of two ways depending on the length of the string. For data strings having run-lengths less than 18 bytes, a cleared offset and the actual run-length are written to an output buffer and then a run bytemore » is written to the output buffer. For data strings of 18 bytes or longer, a set offset and an encoded run-length are written to the output buffer and then a run byte is written to the output buffer. The encoded run-length is written in two parts obtained by dividing the run length by a factor of 255. The first of two parts of the encoded run-length is the quotient; the second part is the remainder. Data bytes that are not part of data strings of sufficient length are written directly to the output buffer.« less
  • The method identifies a Pixon element, which is a fundamental and indivisible unit of information, and a Pixon basis, which is the set of possible functions from which the Pixon elements are selected. The actual Pixon elements selected from this basis during the reconstruction process represents the smallest number of such units required to fit the data and representing the minimum number of parameters necessary to specify the image. The Pixon kernels can have arbitrary properties (e.g., shape, size, and/or position) as needed to best fit the data.
  • The method identifies a Pixon element, which is a fundamental and indivisible unit of information, and a Pixon basis, which is the set of possible functions from which the Pixon elements are selected. The actual Pixon elements selected from this basis during the reconstruction process represents the smallest number of such units required to fit the data and representing the minimum number of parameters necessary to specify the image. The Pixon kernels can have arbitrary properties (e.g., shape size, and/or position) as needed to best fit the data.