A Study on Eye Detection by Using Adaboost for Iris Recognition in Mobile Environments

Adaboost를 이용한 모바일 환경에서의 홍채인식을 위한 눈 검출에 관한 연구

  • 박강령 (동국대학교 전자공학과) ;
  • 박성효 (상명대학교 컴퓨터과학과) ;
  • 조달호 (상명대학교 컴퓨터과학과)
  • Published : 2008.07.25

Abstract

In this paper, we propose the new eye detection method by using adaboost (adaptive boosting) method. Also, to reduce the false alarm rate which identifies the non-eye region as genuine eye that is the Problems of previous method using conventional adaboost, we proposed the post processing methods which used the cornea specular reflection and determined the optimized ratio of eye detecting box. Based on detected eye region by using adaboost, we performed the double circular edge detector for localizing a pupil and an iris region at the same time. Experimental results showed that the accuracy of eye detection was about 98% and the processing time was less than 1 second in mobile device.

본 논문에서는 adaboost(adaptive boosting)를 이용한 눈 검출 알고리즘을 제안한다. 또한 기존의 adaboost를 이용한 눈 검출 알고리즘의 문제점으로 지적된, 실제 눈이 아님에도 불구하고, 눈으로 찾는 오검출율(false alarm rate)를 감소시키기 위해 각막 면에 생성되는 조명의 반사광을 모델링을 통해 추정하고 adaboost의 학습과 눈 검출에 사용되는 박스의 최적의 크기를 실험을 통해 결정하였다. 위의 결과로 검출된 눈 영역을 중심으로 일정 영역에 대하여 동공과 홍채 영역을 원형검출기(circular edge detector)를 이용하여 검출하였다. 실험결과 휴대폰으로 취득한 얼굴영상에서 약 99%의 눈 검출 정확도를 나타내었으며 휴대폰 환경에 적용했을 때 처리시간은 1초 내외 소요됨을 알 수 있었다.

Keywords

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