Journal of the Institute of Electronics Engineers of Korea CI (전자공학회논문지CI)

The Institute of Electronics and Information Engineers (대한전자공학회)
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High Performance Object Recognition with Application of the Size and Rotational Invariant Feature of the Fourier Descriptor to the 3D Information of Edges

푸리에 표현자의 크기와 회전 불변 특징을 에지에 대한 3차원 정보에 응용한 고효율의 물체 인식

  • Wang, Shi (Div. of Electronic & Information Engineering, Chonbuk National University) ;
  • Chen, Hongxin (Div. of Electronic & Information Engineering, Chonbuk National University) ;
  • I, Jun-Ho (Div. of Electronic & Information Engineering, Chonbuk National University) ;
  • Lin, Haiping (Div. of Electronic & Information Engineering, Chonbuk National University) ;
  • Kim, Hyong-Suk (Div. of Electronic & Information Engineering, Chonbuk National University) ;
  • Kim, Jong-Man (Div. of Electronic & Information Engineering, Chonbuk National University)
  • 왕실 (전북대학교 전자정보공학부) ;
  • 진홍신 (전북대학교 전자정보공학부) ;
  • 이준호 (전북대학교 전자정보공학부) ;
  • 임해평 (전북대학교 전자정보공학부) ;
  • 김형석 (전북대학교 전자정보공학부) ;
  • 김종만 (전북대학교 전자정보공학부)
  • Published : 2008.11.25
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Abstract

A high performance object recognition algorithm using Fourier description of the 3D information of the objects is proposed. Object boundaries contain sufficient information for recognition in most of objects. However, it is not well utilized as the key solution of the object recognition since obtaining the accurate boundary information is not easy. Also, object boundaries vary highly depending on the size or orientation of object. The proposed object recognition algorithm is based on 1) the accurate object boundaries extracted from the 3D shape which is obtained by the laser scan device, and 2) reduction of the required database using the size and rotational invariant feature of the Fourier Descriptor. Such Fourier information is compared with the database and the recognition is done by selecting the best matching object. The experiments have been done on the rich database of MPEG 7 Part B.

3 차원 정보로부터 정확한 에지를 추출하고 푸리 변환하여 물체를 인식할 수 있는 고 효율의 물체 인식방법을 제안하였다. 물체의 윤곽은 인식에 유용한 많은 정보를 포함하고 있지만, 정확한 윤곽정보를 얻기가 어려우며, 정확한 윤곽정보를 얻었다고 하더라도 물체의 크기나 방향 마다 윤곽이 달라지기 때문에 물체 인식에 획기적 대안으로 활용되지 못하고 있다. 제안한 물체 인식 알고리즘은 1) 레이저 스캔 디바이스를 사용하여 얻는 3 차원 물체정보로부터 정밀한 물체 윤곽을 획득하고 2) 크기 및 회전 불변한 푸리에 표시 자를 이용하여 윤곽을 표현함으로써, 필요 데이터 베이스의 크기를 대폭 줄인다. 이렇게 얻어진 물체에 대한 푸리에 표식자 정보는 미리 준비된 푸리에 표식자 데이터 베이스로부터 최적 정합되는 물체를 찾아 인식한다. 이 알고리즘은 MPEG7 Part B의 방대한 영상 데이터 베이스를 대상으로 실험하였으며, 그에 대한 결과를 논문에 포함시켰다.

Keywords

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