Automated rock detection and shape analysis from mars rover imagery and 3D point cloud data

Kaichang Di*, Zongyu Yue, Zhaoqin Liu, Shuliang Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

A new object-oriented method has been developed for the extraction of Mars rocks from Mars rover data. It is based on a combination of Mars rover imagery and 3D point cloud data. First, Navcam or Pancam images taken by the Mars rovers are segmented into homogeneous objects with a mean-shift algorithm. Then, the objects in the segmented images are classified into small rock candidates, rock shadows, and large objects. Rock shadows and large objects are considered as the regions within which large rocks may exist. In these regions, large rock candidates are extracted through ground-plane fitting with the 3D point cloud data. Small and large rock candidates are combined and postprocessed to obtain the final rock extraction results. The shape properties of the rocks (angularity, circularity, width, height, and width-height ratio) have been calculated for subsequent geological studies.

Original languageEnglish
Pages (from-to)125-135
Number of pages11
JournalJournal of Earth Science
Volume24
Issue number1
DOIs
Publication statusPublished - Feb 2013

Keywords

  • 3D point cloud data
  • Mars rover
  • rock extraction
  • rover image

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