Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Distinction of Real Face and Photo using Stereo Vision

스테레오비전을 이용한 실물 얼굴과 사진의 구분

  • Shin, Jin-Seob (Dept. of Bioinforamtion, Daejeon Health Sciences College) ;
  • Kim, Hyun-Jung (Dept. of Computer Science and Engineering, Konkuk University) ;
  • Won, Il-Yong (Dept. of Cyber Hacking Security, Seoul Hoseo Technical College)
  • 신진섭 (대전보건대학교 바이오정보과) ;
  • 김현정 (건국대학교 컴퓨터공학과) ;
  • 원일용 (서울호서직업전문학교 사이버해킹보안과)
  • Received : 2014.05.31
  • Accepted : 2014.06.24
  • Published : 2014.07.31
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Abstract

In the devices that leave video records, it is an important issue to distinguish whether the input image is a real object or a photo when securing an identifying image. Using a single image and sensor, which is a simple way to distinguish the target from distance measurement has many weaknesses. Thus, this paper proposes a way to distinguish a simple photo and a real object by using stereo images. It is not only measures the distance to the target, but also checks a three-dimensional effect by making the depth map of the face area. They take pictures of the photos and the real faces, and the measured value of the depth map is applied to the learning algorithm. Exactly through iterative learning to distinguish between the real faces and the photos looked for patterns. The usefulness of the proposed algorithm was verified experimentally.

영상 기록을 남기는 장치들에서 신원을 파악할 수 있는 이미지를 확보할 때 입력 영상이 실물인지 사진인지를 구분하는 것은 중요한 문제이다. 단일 영상과 센서 등을 이용하여 단순하게 대상까지 거리만의 측정으로 구분하는 방법은 많은 약점을 가지고 있다. 따라서 본 논문은 스테레오 영상을 이용하여 관찰대상까지 거리뿐만 아니라, 얼굴영역의 깊이 지도를 만들어 입체감을 체크함으로써 단순 사진과 실물 얼굴을 구별하는 방법에 관한 것을 제안한다. 사진과 실물 얼굴을 촬영하고 여기에서 측정된 깊이지도 값을 이용하여 학습 알고리즘에 적용한다. 반복적인 학습을 통해 정확하게 실물과 사진을 구분하는 패턴을 찾았다. 제안한 알고리즘의 유용성은 실험으로 검증하였다.

Keywords

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