Fission gas bubble identification using MATLAB's image processing toolbox

doi:10.1016/j.matchar.2016.06.010

Title: Fission gas bubble identification using MATLAB's image processing toolbox

Full Record
Other Related Research

Abstract

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.

Authors:

Collette, R. ^[1];

^[1]; Keiser, Jr., D. ^[2]; Miller, B. ^[2]; Madden, J. ^[2]; Schulthess, J. ^[2]

Colorado School of Mines, Golden, CO (United States)
Idaho National Lab. (INL), Idaho Falls, ID (United States)

Publication Date:: 2016-06-08

Research Org.:: Idaho National Lab. (INL), Idaho Falls, ID (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1294583

Report Number(s):: INL/JOU-15-35421
Journal ID: ISSN 1044-5803; PII: S1044580316301760

Grant/Contract Number:: 00140302

Resource Type:: Accepted Manuscript

Journal Name:: Materials Characterization

Additional Journal Information:: Journal Volume: 118; Journal Issue: C; Journal ID: ISSN 1044-5803

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; 36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING; nuclear fuel; MATLAB; automated image analysis; fission bubbles; frequency domain filtration; segmentation

Citation Formats


                    Collette, R., King, J., Keiser, Jr., D., Miller, B., Madden, J., and Schulthess, J. Fission gas bubble identification using MATLAB's image processing toolbox.  United States: N. p., 2016. 
        Web.  doi:10.1016/j.matchar.2016.06.010.

Copy to clipboard


                    Collette, R., King, J., Keiser, Jr., D., Miller, B., Madden, J., & Schulthess, J. Fission gas bubble identification using MATLAB's image processing toolbox.  United States.  doi:10.1016/j.matchar.2016.06.010.

Copy to clipboard


                    Collette, R., King, J., Keiser, Jr., D., Miller, B., Madden, J., and Schulthess, J. Wed .  
        "Fission gas bubble identification using MATLAB's image processing toolbox".  United States.  doi:10.1016/j.matchar.2016.06.010.  https://www.osti.gov/servlets/purl/1294583.

Copy to clipboard


                    
@article{osti_1294583,

  title        = {Fission gas bubble identification using MATLAB's image processing toolbox},

  author       = {Collette, R. and King, J. and Keiser, Jr., D. and Miller, B. and Madden, J. and Schulthess, J.},

  abstractNote = {Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.},

  doi          = {10.1016/j.matchar.2016.06.010},

  journal      = {Materials Characterization},

  number       = C,

  volume       = 118,

  place        = {United States},

  year         = {2016},

  month        = {6}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

DOI: 10.1016/j.matchar.2016.06.010

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 1 work

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Fission gas bubble identification using MATLAB's image processing toolbox

Journal Article Collette, R. ; King, J., E-mail: kingjc@mines.edu ; Keiser, D. ; ... - Materials Characterization

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore »« less
DOI: 10.1016/J.MATCHAR.2016.06.010
Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Journal Article Collette, R. ; Douglas, J. ; Patterson, L. ; ... - Materials Characterization

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellularmore »« less
DOI: 10.1016/J.MATCHAR.2015.03.034
Benefits of utilizing CellProfiler as a characterization tool for U-10Mo nuclear fuel

Journal Article Collette, R. ; Douglas, J. ; Patterson, L. ; ... - Materials Characterization

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium-molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellularmore »« less
Cited by 1
DOI: 10.1016/j.matchar.2015.03.034

Full Text Available
Analysis of irradiated U-7wt%Mo dispersion fuel microstructures using automated image processing

Journal Article Collette, R. ; King, J. ; Buesch, C. ; ... - Journal of Nuclear Materials

The High Performance Research Reactor Fuel Development (HPPRFD) program is responsible for developing low enriched uranium (LEU) fuel substitutes for high performance reactors fueled with highly enriched uranium (HEU) that have not yet been converted to LEU. The uranium-molybdenum (U-Mo) fuel system was selected for this effort. In this study, fission gas pore segmentation was performed on U-7wt%Mo dispersion fuel samples at three separate fission densities using an automated image processing interface developed in MATLAB. Pore size distributions were attained that showed both expected and unexpected fission gas behavior. In general, it proved challenging to identify any dominant trends whenmore »« less
DOI: 10.1016/j.jnucmat.2016.03.028

Full Text Available
Characterization of fission gas bubbles in irradiated U-10Mo fuel

Journal Article Casella, Andrew M. ; Burkes, Douglas E. ; MacFarlan, Paul J. ; ... - Materials Characterization

A simple, repeatable method for characterization of fission gas bubbles in irradiated U-Mo fuels has been developed. This method involves mechanical potting and polishing of samples along with examination with a scanning electron microscope located outside of a hot cell. The commercially available software packages CellProfiler, MATLAB, and Mathematica are used to segment and analyze the captured images. The results are compared and contrasted. Finally, baseline methods for fission gas bubble characterization are suggested for consideration and further development.
Cited by 1
DOI: 10.1016/J.MATCHAR.2017.06.007

Full Text Available

Similar Records