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CNN을 적용한 조명변화에 강인한 얼굴인식 연구

Research on Robust Face Recognition against Lighting Variation using CNN

  • 투고 : 2017.02.02
  • 심사 : 2017.04.24
  • 발행 : 2017.04.30

초록

얼굴인식 기술은 지난 수십 년간 연구되어온 분야로서 보안, 엔터테인먼트, 모바일 서비스 등 다양한 영역에서 활용되고 있다. 얼굴인식 기술이 가진 주된 문제점은 밝기, 조명각도, 영상 회전등의 환경적 변화 요소에 따라 인식률이 현저하게 감소된다는 것이다. 따라서 본 논문에서는 최근 많은 계산량을 처리할 수 있는 컴퓨터 하드웨어와 알고리즘의 발전으로 재조명 받고 있는 CNN을 이용해 조명변화에 강인한 얼굴인식 방법을 제안하였다. 이후 성능검증을 위해 기존의 얼굴인식 알고리즘인 PCA, LBP, DCT와 결과 비교를 진행하였으며, 각각 9.82%, 11.6%, 4.54%의 성능 향상을 보였다. 또한 기존 신경망을 적용한 얼굴인식 연구결과 비교에서도 5.24%의 성능 향상을 기록하여 최종 인식률 99.25%를 달성하는 결과를 보였다.

과제정보

연구 과제 주관 기관 : 순천대학교

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