Journal of Broadcast Engineering (방송공학회논문지)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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Gabor Descriptors Extraction in the SURF Feature Point for Improvement Accuracy in Face Recognition

얼굴 인식의 정확도 향상을 위한 SURF 특징점에서의 Gabor 기술어 추출

  • 이재용 (광운대학교 VIA-멀티미디어 센터) ;
  • 김지은 (광운대학교 VIA-멀티미디어 센터) ;
  • 오승준 (광운대학교 VIA-멀티미디어 센터)
  • Received : 2012.05.03
  • Accepted : 2012.09.07
  • Published : 2012.09.30
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Abstract

Face recognition has been actively studied and developed in various fields. In recent years, interest point extraction algorithms mainly used for object recognition were being applied to face recognition. The SURF(Speeded Up Robust Features) algorithm was used in this paper which was one of typical interest point extraction algorithms. Generally, the interest points extracted from human faces are less distinctive than the interest points extracted from objects due to the similar shapes of human faces. Thus, the accuracy of the face recognition using SURF tends to be low. In order to improve it, we propose a face recognition algorithm which performs interest point extraction by SURF and the Gabor wavelet transform to extract descriptors from the interest points. In the result, the proposed method shows around 23% better recognition accuracy than SURF-based conventional methods.

얼굴 인식은 여러 분야에서의 활발한 연구를 통해 많은 발전이 있었고, 현재도 활발한 연구가 진행되고 있다. 최근 들어 물체 인식에 주로 사용되어온 특징점 추출 알고리즘이 얼굴 인식에도 적용되고 있다. 본 논문은 대표적인 특징점 추출 알고리즘인 SURF를 이용한다. 사람은 얼굴의 형태 및 구조가 유사하므로 물체를 인식하는 경우보다 분별력이 떨어지기 때문에 SURF를 이용한 얼굴인식의 정확도는 낮은 편이다. 이를 개선하고자 본 논문에서는 SURF를 통해 추출한 특징점에서 Gabor 웨이블릿 변환을 사용해 기술어를 추출하는 얼굴 인식 방법을 제안한다. 실험 결과에서 제안하는 방법이 기존 SURF 기반의 얼굴 인식에 비해 정확도가 약 23% 향상된 것을 확인하였다.

Keywords

References

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