Journal of Broadcast Engineering (방송공학회논문지)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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Illumination Robust Feature Descriptor Based on Exact Order

조명 변화에 강인한 엄격한 순차 기반의 특징점 기술자

  • Kim, Bongjoe (School of Electrical and Elctronic Engineering, Yonsei University) ;
  • Sohn, Kwanghoon (School of Electrical and Elctronic Engineering, Yonsei University)
  • 김봉조 (연세대학교 전기전자공학부) ;
  • 손광훈 (연세대학교 전기전자공학부)
  • Received : 2012.10.29
  • Accepted : 2012.12.14
  • Published : 2013.01.30
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Abstract

In this paper, we present a novel method for local image descriptor called exact order based descriptor (EOD) which is robust to illumination changes and Gaussian noise. Exact orders of image patch is induced by changing discrete intensity value into k-dimensional continuous vector to resolve the ambiguity of ordering for same intensity pixel value. EOD is generated from overall distribution of exact orders in the patch. The proposed local descriptor is compared with several state-of-the-art descriptors over a number of images. Experimental results show that the proposed method outperforms many state-of-the-art descriptors in the presence of illumination changes, blur and viewpoint change. Also, the proposed method can be used for many computer vision applications such as face recognition, texture recognition and image analysis.

컴퓨터 비전에서 두 영상 사이에 대응점을 찾는 영상 정합 성능은 조명 변화에 큰 영향을 받는다. 본 논문에서는 조명 변화 문제와 기존 순차 기반 기술자의 단점을 해결하기 위하여, 엄격한 순차 기반의 특징점 기술자를 제안한다. 제안하는 기술자는 관심영역내 모든 픽셀의 순차 정보를 이용하여 기술자를 추출한다. 동일한 픽셀 값의 순차 모호성을 해결하기 위하여, 제안하는 방법은 불연속 스칼라 픽셀 값을 k차수의 연속적인 벡터 값으로 변환한다. k차수의 벡터 값으로부터 계산된 엄격한 순차를 이용하여 특징점 기술자를 추출하였으며, 이를 이용하여 영상 정합을 수행하였다. 실험결과 제안한 방법은 영상의 밝기 왜곡 및 가우시안 노이즈에 기존의 방법보다 강건한 영상 정합 성능을 나타낸다. 제안한 방법은 조명 변화에 강인한 특징점을 표현하는 기술로써 영상 정합과 더불어 얼굴인식, 텍스처 검출 및 영상 분석에 활용될 수 있다.

Keywords

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