Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

An improved recognition algorithm for lunar terrain based on CCD image

Authors
Zhankai Li, Jiaheng Chen, Yiren Chang, Xiaolin Tian
Corresponding Author
Zhankai Li
Available Online March 2016.
DOI
https://doi.org/10.2991/icmmct-16.2016.315How to use a DOI?
Keywords
CCD image; Recognition algorithm; Lunar terrain; Mare and Highland
Abstract
With the development of space technology, topographic study of celestial bodies becomes increasingly important. In order to better carry out geomorphologic analysis and landing site selection of celestial bodies, the terrain classification becomes particularly critical. This paper provides an improved algorithm and proved its better in identifying the lunar mare area and the highland area of the CCD images with four features used in k-means clustering. We chose two typical areas: ‘H010’ and ‘SI’ areas of lunar terrain to research. And the result of the improved algorithm is analyzed from two different block size with different number of testing points. And also the whole recognition rate and Cohen’s kappa coefficient are both better than the result of previous algorithm in using DEM or CCD data. Especially in the ‘H010’ area, the average whole recognition rate is 91.4325%, and the average Cohen’s kappa coefficient is 0.813.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 4th International Conference on Machinery, Materials and Computing Technology
Part of series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/icmmct-16.2016.315How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zhankai Li
AU  - Jiaheng Chen
AU  - Yiren Chang
AU  - Xiaolin Tian
PY  - 2016/03
DA  - 2016/03
TI  - An improved recognition algorithm for lunar terrain based on CCD image
BT  - 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1580
EP  - 1586
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.315
DO  - https://doi.org/10.2991/icmmct-16.2016.315
ID  - Li2016/03
ER  -