Automatic identification and extraction of impact craters in the landing area of Chang'e-5 based on HOG features and SVM

Yilan Lou; Siheng Ren; Junfeng Xu; Jingli Jiang

doi:10.1117/12.2604634

5 October 2021 Automatic identification and extraction of impact craters in the landing area of Chang'e-5 based on HOG features and SVM

Yilan Lou, Siheng Ren, Junfeng Xu, Jingli Jiang

Author Affiliations +

Proceedings Volume 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning; 119110Z (2021) https://doi.org/10.1117/12.2604634
Event: 2nd International Conference on Computer Vision, Image and Deep Learning, 2021, Liuzhou, China

Abstract

The Moon is the heavenly body closest to Earth. In order to conduct an in-depth study on the Moon, select the landing site, and/or plan for roving exploration, researchers need to understand how long the Moon has existed and how it was formed. An internationally common method for age dating of the Moon in areas without lunar soil samples is to determine the absolute age of the Moon based on the number and sizes of impact craters. For the identification and extraction of impact craters required for age dating, we combined histogram of oriented gradients (HOG) features and support-vector machine (SVM) classifiers to set up a sample pool (including positive and negative samples) for lunar impact craters, thereby achieving automatic identification and extraction of impact craters of different sizes in the landing area of Chang'e-5.

Citation Download Citation

Yilan Lou, Siheng Ren, Junfeng Xu, and Jingli Jiang "Automatic identification and extraction of impact craters in the landing area of Chang'e-5 based on HOG features and SVM", Proc. SPIE 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning, 119110Z (5 October 2021); https://doi.org/10.1117/12.2604634

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