The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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Adaptive Image Labeling Algorithm Using Non-recursive Flood-Fill Algorithm

비재귀 Flood-Fill 알고리즘을 이용한 적응적 이미지 Labeling 알고리즘

  • Kim, Do-Hyeon (Dept.of Computer Science, Graduate School of Busan National University) ;
  • Gang, Dong-Gu (Dept.of Computer Science, Graduate School of Busan National University) ;
  • Cha, Ui-Yeong (Dept.of Computer Science, Busan National University)
  • 김도현 (부산대학교 대학원 전자계산학과) ;
  • 강동구 (부산대학교 대학원 전자계산학과) ;
  • 차의영 (부산대학교 전자계산학과)
  • Published : 2002.06.01
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Abstract

This paper proposes a new adaptive image labeling algorithm fur object analysis of the binary images. The proposed labeling algorithm need not merge/order of complex equivalent labels like classical labeling algorithm and the processing is done during only 1 Pass. In addition, this algorithm can be extended for gray-level image easily. Experiment result with HIPR image library shows that the proposed algorithm process more than 2 times laster than compared algorithm.

본 논문에서는 이진화 영상의 물체 분석에서 자주 사용되는 새로운 Labeling 알고리즘을 제안한다. 제안한 Labeling 알고리즘은 기존의 Labeling 과는 달리 복잡한 Equivalent Labeling Merging/Ordering이 필요하지 않으며 비재귀적인 Flood-filling에 의하여 1 pass에 Labeling이 이루어진다. 또한 Gray-level 이미지에 대해서도 쉽게 확장될 수 있으며, HIPR Image Library를 대상으로 실험한 결과 기존의 방법보다 2배 이상의 빠른 수행 속도를 보였다.

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References

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