The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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Content-based Image Retrieval Using Fuzzy Multiple Attribute Relational Graph

퍼지 다중특성 관계 그래프를 이용한 내용기반 영상검색

  • 정성환 (국립창원대학교 컴퓨터공학과)
  • Published : 2001.10.01
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Abstract

In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.

본 연구에선는 FAGA(Fuzzy Attribute Relational Graph) 노드의 단일특성을 실제 영상을 응용하여 다중특성으로 확장하고, 노드의 레이블뿐만 아니라, 칼라 질감 그리고 공간관계를 고려한 다중특성 관계 그래프를 이용한 새로운 영상검색을 제안하였다. 1,240 개의 영상으로 구성된 합성영상 데이터베이스와 NETRA 및 Corel Drew 의 1,026개의 영상으로 구성된 자연영상 데이터베이스를 사용하여 실험한 결과, 다중특성을 고려한 접근방법이 단일 특성만 고려하는 방법에 비하여, 합성영상의 경우 Recall에서 6~30% 성능 증가를 보였고, 자연연상의 경우에도 Displacement 척도들과 유사 검색 영상의 수에서 검색 성능이 우수함을 실험을 통하여 확인하였다.

Keywords

References

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