z-logo
Premium
A methodology for the semi‐automatic digital image analysis of fragmental impactites
Author(s) -
Chanou A.,
Osinski G. R.,
Grieve R. A. F.
Publication year - 2014
Publication title -
meteoritics and planetary science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.09
H-Index - 100
eISSN - 1945-5100
pISSN - 1086-9379
DOI - 10.1111/maps.12267
Subject(s) - digital image analysis , digital image , geology , image (mathematics) , software , computer science , digital image processing , image processing , dimension (graph theory) , artificial intelligence , computer graphics (images) , pattern recognition (psychology) , mineralogy , computer vision , mathematics , combinatorics , programming language
A semi‐automated digital image analysis method is developed for the comparative textural study of impact melt‐bearing breccias. This method uses the freeware software ImageJ developed by the National Institute of Health (NIH). Digital image analysis is performed on scans of hand samples (10–15 cm across), based on macroscopic interpretations of the rock components. All image processing and segmentation are done semi‐automatically, with the least possible manual intervention. The areal fraction of components is estimated and modal abundances can be deduced, where the physical optical properties (e.g., contrast, color) of the samples allow it. Other parameters that can be measured include, for example, clast size, clast‐preferred orientations, average box‐counting dimension or fragment shape complexity, and nearest neighbor distances (NnD). This semi‐automated method allows the analysis of a larger number of samples in a relatively short time. Textures, granulometry, and shape descriptors are of considerable importance in rock characterization. The methodology is used to determine the variations of the physical characteristics of some examples of fragmental impactites.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom