Scale-Space 이론에 기초한 내용 기반 영상 검색

Content-Based Image Retrieval using Scale-Space Theory

  • 발행 : 1999.01.01

초록

In this paper, a content-based image retrieval scheme based on scale-space theory is proposed. The existing methods using scale-space theory consider all scales for image retrieval,thereby requiring a lot of computation. To overcome this problem, the proposed algorithm utilizes amodified histogram intersection method to select candidate images from database. The relative scalebetween a query image and a candidate image is calculated by the ratio of histograms. Feature pointsare extracted from the candidates using a corner detection algorithm. The feature vector for eachfeature point is composed of RGB color components and differential invariants. For computing thesimilarity between a query image and a candidate image, the euclidean distance measure is used. Theproposed image retrieval method has been applied to various images and the performance improvementover the existing methods has been verified.

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참고문헌

  1. IEEE Computer v.28 no.9 Query by Image and Video Content: The QBIC System M.Flickner;H.Sawhney;W.Niblack;J.Ashley;Q.Huang;B.Dom;M.Gorkani;J.Hafner; D.Lee;D.Petkovic;D.Steel;P.Yanker
  2. International Journal of Computer Vision v.7 no.1 Color Indexing M.J.Swain;D.H.Ballard
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  6. IEEE TRANS.Pattern Analysis and Machine Intelligence v.19 no.5 Local Grayvalues Invariants for Image Retrieval C.Schmid;R.Mohr
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  8. Technical Report INIRA v.2644 Matching by Local Invariants C.Schmid;R.Mohr
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