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

• Published in: Journal of earth science (Wuhan, China) Vol. 24; no. 1; pp. 125 - 135
• Main Author: 邸凯昌 岳宗玉 刘召芹 王树良
• Format: Journal Article
• Language: English
• Published: China University of Geosciences China University of Geosciences 01.02.2013; Springer Nature B.V
• Subjects: Biogeosciences; Earth and Environmental Science; Earth science; Earth Sciences; Geochemistry; Geology; Geotechnical Engineering & Applied Earth Sciences; Mars; Planetology; Rocks; Scientific imaging; Space exploration; 三维; 候选人; 图像; 形状分析; 检测; 火星岩石; 火星探测器; 点云数据; rover image; Mars rover; 3D point cloud data; rock extraction
• ISSN: 1674-487X; 1867-111X
• DOI: 10.1007/s12583-013-0316-3

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 ~eological studies.