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U.S. Department of Energy
Office of Scientific and Technical Information

Image Analysis: Comparison Metrics

Technical Report ·
DOI:https://doi.org/10.2172/1765865· OSTI ID:1765865
 [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Despite an increased reliance on computational modeling in engineering and physics, graphically comparing computational and experimental results has often been qualitative, via a so-called ‘viewgraph norm’. Image recognition, computer vision and artificial intelligence (AI) are fields of study in themselves and rapidly progressing, but relying on AI to grade image similarity evokes a notion of asking for an expert judgement, which could be seen as an artificial version of the viewgraph norm. It is, therefore, desirable to use simpler metrics which are more tractable and unambiguous, even though they may not be as ‘intelligent.’ In this document, a few metrics are studied by systematically altering an image and their implications are analyzed
Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
89233218CNA000001
OSTI ID:
1765865
Report Number(s):
LA-UR-21-21459
Country of Publication:
United States
Language:
English

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