Using computer-aided image processing to estimate chemical composition of igneous rocks: A potential tool for large-scale compositional mapping

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: http://doi.org/10.1016/j.sesci.2020.12.003. This is version 3 of this Preprint.

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Authors

Julin Zhang, Cin-Ty A. Lee, Michael Farner

Abstract

Digital cameras, particularly on smartphones, have led to the proliferation of amateur photographers. Of interest here is the use of smartphone cameras to conduct rapid, low-cost compositional mapping of geologic bedrock, such as plutons and batholiths, in combination with chemical analyses of rocks in the laboratory. This paper discusses some of the challenges in geochemical mapping using image analysis. We discuss methods for color calibration through a series of experiments under different light intensities and conditions (spectra). All indoor and outdoor experiments show good reproducibility, but suffer from biases imparted by different light intensities, light conditions, and camera exposure times. These biases can be greatly reduced with a linear color calibration method. Over-exposed and under-exposed images, however, cannot be fully calibrated, so we discuss methods that ensure images are properly exposed. We applied our method to 59 natural granitoid samples of known chemical composition. Strong correlations between average gray levels and major element compositions were observed, indicating that very subtle variations in bulk composition can potentially be rapidly assessed using calibrated photographs of outcrops.

DOI

https://doi.org/10.31223/osf.io/s92rg

Subjects

Earth Sciences, Geochemistry, Geology, Physical Sciences and Mathematics

Keywords

geochemistry, Image processing, color calibration, mapping

Dates

Published: 2020-02-20 12:09

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License

GNU Lesser General Public License (LGPL) 2.1