한국군사과학기술학회지 (Journal of the Korea Institute of Military Science and Technology)

  • 제23권2호
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  • Pages.139-146
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  • 2020
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  • 1598-9127(pISSN)
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  • 2636-0640(eISSN)
한국군사과학기술학회 (The Korea Institute of Military Science and Technology)
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적록색맹 모사 영상 데이터를 이용한 딥러닝 기반의 위장군인 객체 인식 성능 향상

Performance Improvement of a Deep Learning-based Object Recognition using Imitated Red-green Color Blindness of Camouflaged Soldier Images

  • 최근하 (육군교육사령부 인공지능연구발전처)
  • Choi, Keun Ha (Artificial Intelligence Research & Development Center, Army Training and Doctrine Command)
  • 투고 : 2020.01.20
  • 심사 : 2020.03.30
  • 발행 : 2020.04.05
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초록

The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

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참고문헌

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