우주기술과 응용 (Journal of Space Technology and Applications)

  • 제1권1호
  • /
  • Pages.49-63
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  • 2021
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  • 2799-3213(pISSN)
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  • 2765-7469(eISSN)
한국우주과학회 (The Korean Space Science Society)
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딥러닝을 이용한 달 크레이터 탐지

Lunar Crater Detection using Deep-Learning

  • 투고 : 2021.05.19
  • 심사 : 2021.05.19
  • 발행 : 2021.05.31
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⟨ 이전 논문 다음 논문 ⟩

초록

태양계 천체 탐사는 다양한 탑재체를 통해 이루어지고 있고, 그에 따라 많은 연구 결과들이 나오고 있다. 우리는 태양계 천체 연구의 한 방법으로 딥러닝 적용을 시도해 보았다. 지구 관측 위성 자료와 다르게 태양계 천체 자료들은 천체들에 따라 탐사선에 따라 각 탐사선의 탑재체에 따라 그 자료의 형태가 매우 다르다. 그래서 학습시킨 모델로 다양한 자료에 적용이 어려울 수 있지만 사람에 의한 오류를 줄이거나, 놓치는 부분들을 보완해 줄 수 있을 것이라고 기대한다. 우리는 달 표면의 크레이터를 탐지하는 모델을 구현해 보았다. Lunar Reconnaissance Orbiter Camera (LROC) 영상과 제공하는 shapefile을 입력값으로 하여 모델을 만들었고, 이를 달 표면 영상에 적용하여 보았다. 결과가 만족스럽지는 못했지만 이후 이미지 전처리와 모델 수정 작업을 통해 최종적으로는 ShadowCam에 의해 획득되는 달의 영구음영지역 영상에 적용할 예정이다. 이 외에도 달 표면과 비슷한 형태를 가진 세레스와 수성에 적용을 시도하여 딥러닝이 태양계 천체 연구에 또 다른 방법임을 시사하고자 한다.

The exploration of the solar system is carried out through various payloads, and accordingly, many research results are emerging. We tried to apply deep-learning as a method of studying the bodies of solar system. Unlike Earth observation satellite data, the data of solar system differ greatly from celestial bodies to probes and to payloads of each probe. Therefore, it may be difficult to apply it to various data with the deep-learning model, but we expect that it will be able to reduce human errors or compensate for missing parts. We have implemented a model that detects craters on the lunar surface. A model was created using the Lunar Reconnaissance Orbiter Camera (LROC) image and the provided shapefile as input values, and applied to the lunar surface image. Although the result was not satisfactory, it will be applied to the image of the permanently shadow regions of the Moon, which is finally acquired by ShadowCam through image pre-processing and model modification. In addition, by attempting to apply it to Ceres and Mercury, which have similar the lunar surface, it is intended to suggest that deep-learning is another method for the study of the solar system.

키워드

과제정보

본 과제는 한국연구재단(NRF)의 지원을 받아서 연구를 수행하였습니다(2018M1A3A3A02065832).

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