A Feature Selection Method for Craters in Martian Terrain Matching

TAO Jiang; CAO Yun-feng; DING Meng; ZHUANG Li-kui; ZHANG Zhou-yu; ZHONG Pei-yi

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A Feature Selection Method for Craters in Martian Terrain Matching

更新时间：2026-09-04

- A Feature Selection Method for Craters in Martian Terrain Matching
- Vol. 34, Issue 9, Pages: 82-86(2017)
- 作者机构：
  
  1. 南京航空航天大学航天学院,江苏,南京,210016
  2. 南京航空航天大学民航学院,江苏,南京,210016
- 作者简介：
- 基金信息：
- DOI：
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- Published：2017
- 稿件说明：
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陶江, 曹云峰, 丁萌, 庄丽葵, 张洲宇, 钟佩仪. 一种用于火星地形匹配的撞击坑特征选择方法[J]. 微电子学与计算机, 2017, 34(9): 82-86, 91.

TAO Jiang, CAO Yun-feng, DING Meng, et al. A Feature Selection Method for Craters in Martian Terrain Matching[J]. 2017, 34(9): 82-86.
陶江, 曹云峰, 丁萌, 庄丽葵, 张洲宇, 钟佩仪. 一种用于火星地形匹配的撞击坑特征选择方法[J]. 微电子学与计算机, 2017, 34(9): 82-86, 91. DOI：

TAO Jiang, CAO Yun-feng, DING Meng, et al. A Feature Selection Method for Craters in Martian Terrain Matching[J]. 2017, 34(9): 82-86. DOI：

摘要

火星探测器在着陆过程中面临严峻的火星地理环境

对特征提取及特征匹配的性能造成严重影响.为此

提出了一种多特征融合的撞击坑特征选择方法.该方法先对撞击坑用多种特征检测子进行可重复性评价得出综合性能最好的AKAZE特征检测子

然后以AKAZE特征检测子为基础

通过查全率-查错率(recall vs.1-precision) 曲线来对多种特征描述子评价

最后将其中性能较好的一种或几种特征结合

对撞击坑地貌进行特征提取及匹配

选择匹配性能最好的一组作为撞击坑匹配定位的特征.实验结果表明

用该特征选择方法进行撞击坑匹配与传统的SIFT特征匹配相比

匹配正确率提高了8%左右.

Abstract

Mars spacecraft facing severe Mars geographical environment in the landing process.Performance of feature extraction and feature matching have been seriously affected.To solve this problem

a feature selection method based on multi-feature fusion is proposed.Firstly

the AKAZE feature detector with the best comprehensive performance is obtained by using the repeatability evaluation of the feature pits.Then

based on the AKAZE feature detector

the recall rate 1-precision curve is used to evaluate the feature descriptors.Finally

one or several features with better performance are combined to extract and match the features of the craters

and the best matching performance is selected as the feature of positioning for crater.Experimental results show that compared with the traditional SIFT feature matching

the matching accuracy is improved by about 8%.

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references

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朱英红. 基于特征的红外与可见光图像匹配技术研究[D]. 西安: 第二炮兵工程大学, 2012.

Cheng Y, Ansar A. Landmark based position estimation for pinpoint landing on mars[C]//IEEE International Conference on Robotics and Automation. IEEE, 2005: 4470.

Mikolajczyk K, Schmid C. A performance evaluation of local descriptors[C]//IEEE Computer Society Conference on Computer Vision % Pattern Recognition. IEEE, 2003.

Trawny N, Mourikis A I, Roumeliotis S I. Vision-aided inertial navigation for pin-point landing using observations of mapped landmarks[J]. Journal of Field Robotics, 2007, 24: 357-78. DOI: 357

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Golombek M, Grant J, Kipp D. Selection of the mars scie-nce laboratory landing site[J]. Space Science Reviews: 2012, 170: 1. DOI: 1

Cheng Y, Andrew E J, Larry H M. Optical landmark detection for spacecraft navigation[J]. Advances in the Astronautical Sciences: 2003, 114(3): 1785-1803. DOI: 1785

Cordes K, Grundmann L, Ostermann J. Feature evaluation with high-resolution images[C]//Computer Analysis of Images and Patterns. Springer International Publishing, 2015, 9256: 374-386.

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