항공우주시스템공학회지 (Journal of Aerospace System Engineering)

  • 제16권5호
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  • Pages.70-77
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  • 2022
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  • 1976-6300(pISSN)
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  • 2508-7150(eISSN)
항공우주시스템공학회 (The Society for Aerospace System Engineering)
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미소 픽셀을 갖는 비행 객체 인식을 위한 데이터베이스 구축 및 관리시스템 연구

Database Generation and Management System for Small-pixelized Airborne Target Recognition

  • 이호섭 (청주대학교 일반대학원 기계항공시스템공학과) ;
  • 신희민 (한국항공우주연구원 무인기연구부) ;
  • 심현철 (한국과학기술원 전기및전자공학부) ;
  • 조성욱 (청주대학교 항공학부 항공기계공학전공)
  • Lee, Hoseop (Department of mechanical and Aerospace Engineering of Cheongju University) ;
  • Shin, Heemin (School of Electrical Engineering, KAIST) ;
  • Shim, David Hyunchul (Unmanned Aircraft System Research Division, Korea Aerospace Research Institute) ;
  • Cho, Sungwook (Department of Aeromechnical Engineering of Cheongju University)
  • 투고 : 2022.06.02
  • 심사 : 2022.07.19
  • 발행 : 2022.10.31
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초록

본 논문에서, 데이터베이스 생성 및 관리 시스템은 미소 픽셀 공중 표적 인식을 위해 제안된다. 제안된 시스템은 1)비행 테스트 비디오 프레임에 의한 직접 이미지 추출, 2) 자동 이미지 보관, 3) 이미지 데이터 레이블링 및 메타 데이터 주석, 4) 컬러 채널 변환, 5) HOG/LBP 기반 소화소 대상 증강 이미지 데이터 생성의 다섯가지 주요 기능으로 구성된다. 제안하는 프로그램은 파이썬 기반의 PyQt5와 OpenCV를 이용하여 구성하였고 공중 표적 인식을 위한 이미지 데이터셋은 제안한 시스템을 이용해 생성했으며 비행 실험으로 부터 수집된 영상을 입력영상으로 사용하였다.

This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.

키워드

과제정보

1. 이 논문은 2021~2022년도 청주대학교 연구장학 지원에 의한 것임 2. 본 연구는 다부처사업으로 한국연구재단의 '드론캅 기체/요소기술 및 운용시스템 개발(NFR-2021M3C1C4039579)' 과제의 지원을 받아 수행되었습니다.

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