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Volume 24 Issue 1
Feb 2013
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Kaichang Di, Zongyu Yue, Zhaoqin Liu, Shuliang Wang. Automated Rock Detection and Shape Analysis from Mars Rover Imagery and 3D Point Cloud Data. Journal of Earth Science, 2013, 24(1): 125-135. doi: 10.1007/s12583-013-0316-3
Citation: Kaichang Di, Zongyu Yue, Zhaoqin Liu, Shuliang Wang. Automated Rock Detection and Shape Analysis from Mars Rover Imagery and 3D Point Cloud Data. Journal of Earth Science, 2013, 24(1): 125-135. doi: 10.1007/s12583-013-0316-3

Automated Rock Detection and Shape Analysis from Mars Rover Imagery and 3D Point Cloud Data

doi: 10.1007/s12583-013-0316-3
Funds:

the National Natural Science Foundation of China 41171355

the National Natural Science Foundation of China 41002120

More Information
  • Corresponding author: Kaichang Di: kcdi@irsa.ac.cn
  • Received Date: 19 Jun 2012
  • Accepted Date: 11 Oct 2012
  • Publish Date: 01 Feb 2013
  • 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.

     

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