IFS fractal code for image retrieval on compression domain

  • Authors:

  • Liangbin Zhang;Lule Zhang;Lifeng Xi;Kun Gao;Tianyun Hu

  • Affiliations:

  • Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P.R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P.R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P.R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P.R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P.R. China

  • Venue:
  • CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
  • Year:
  • 2009

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Abstract

Digital image databases represent huge amount of data, automatic indexing and content base retrieval are crucial factors. IFS ( Iterated function system ) fractal code can be used to retrieve image and the position parameter of IFS code is replaced with the relative distance and direction parameter. A new algorithm of IFS fractal code for image retrieval on compression domain is presented in this paper. First, the inquired image and each image in the database are encoded by Jacquin fractal coding. Second, the image fractal feature vector and the distance of fractal code between two images are defined, and the distance between the inquired image and current image in the database are computed one by one. Finally, the preceding n frame images which are the smallest distance sum of fractal code are taken as the retrieval result. Experimental results show that compared with the direct image pixels similar matching strategy, our scheme shortens the retrieval time of compression domain greatly and guarantees the retrieval accuracy. Our proposed method is effective and feasible.