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Segmenting images automatically for granulometry and sedimentology: a martian case study

Icarus

By:
, , , , ,
DOI: 10.1016/j.icarus.2013.09.021

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Abstract

In a companion work, we bridge the gap between mature segmentation software used in terrestrial sedimentology and emergent planetary segmentation with an original algorithm optimized to segment whole images from the Microscopic Imager (MI) of the Mars Exploration Rovers (MER). In this work, we compare its semi-automated outcome with manual photoanalyses using unconsolidated sediment at Gusev and Meridiani Planum sites for geologic context. On average, our code and manual segmentation converge to within ~10% in the number and total area of identified grains in a pseudo-random, single blind comparison of 50 samples. Unlike manual segmentation, it also locates finer grains in an image with internal consistency, enabling robust comparisons across geologic contexts. When implemented in Mathematica- 8, the algorithm segments an entire MI image within minutes, surpassing the extent and speed possible with manual segmentation by about a factor of ten. These results indicate that our algorithm enables not only new sedimentological insight from the MER MI data, but also detailed sedimentology with the Mars Science Laboratory’s Mars Hand Lens Instrument.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Segmenting images automatically for granulometry and sedimentology: a martian case study
Series title:
Icarus
DOI:
10.1016/j.icarus.2013.09.021
Year Published:
2013
Language:
English
Publisher:
Elsevier
Description:
10 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
408
Last page:
417