Open AccessCEmin: A MATLAB‐Based Software for Computational Phenocryst Extraction and Statistical Petrology
Author(s) -
Zeng Ling,
Cheng Lilu,
Costa Fidel,
Herrin Jason
Publication year - 2018
Publication title -
geochemistry, geophysics, geosystems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.928
H-Index - 136
ISSN - 1525-2027
DOI - 10.1002/2017gc007346
Subject(s) - plagioclase , phenocryst , petrography , matlab , geology , electron microprobe , software , computer science , compositional data , mineralogy , quartz , machine learning , operating system , paleontology , programming language
It is nowadays common to collect large‐area backscattered electron images and X‐ray maps of entire standard petrographic thin sections. These images can be calibrated for compositions of some minerals (e.g., plagioclase) with a small number of electron microprobe analyses, and thus provide a wealth of quantitative data for hundreds of crystals. However, to effectively make use of the textures and compositions of large numbers of crystals we need to be able to efficiently outline and segregate the crystals of interest from the rest of the sample. Here we present CEmin, a set of MATLAB routines that are user‐friendly and allow users to semiautomatically separate plagioclase crystals in grayscale images of volcanic rocks for further processing. These data can then be used for textural and chemical zoning studies. Efficiently extracting large amounts of crystal data allows for identification of plagioclase populations that are indicative of magmatic processes (e.g., closed versus open system) and statistical comparison to thermodynamic models.