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Title: Optimizing Segmentation for Quantitative Studies of Materials

An increasing amount of image data is being produced. Currently, most of the anlysis is done manually. There is a growing need to automate image interpretation.
Authors:
 [1] ;  [1] ;  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
OSTI Identifier:
1296631
Report Number(s):
LA-UR--16-25697
DOE Contract Number:
AC52-06NA25396
Resource Type:
Technical Report
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 36 MATERIALS SCIENCE Computer Science; Mathematics; Material Science; image segmentation, active contours, level sets, materials images, structural characterization