Fast indexing and searching for content-based image retrieval

J. You, H. Shen

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


This paper presents a general approach to fast image indexing and searching for content-based image retrieval on a network of workstation clusters. Three primary issues in image retrieval are discussed: image feature extraction and representation, similarity measure, and searching methods. A wavelet based image feature extraction scheme is introduced to represent images with multiple features such as colours, textures and shapes. In addition, a feature component code is proposed to facilitate a dynamic image indexing scheme where images are queried by different features or combinations. Furthermore, the relevance feedback technique for information retrieval is used to convert image feature vectors to weight-term vectors for efficient searching.

Original languageEnglish
Pages (from-to)212-218
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 6 Jul 1998
Externally publishedYes
EventVisual Information Processing VII 1998 - Orlando, United States
Duration: 13 Apr 199817 Apr 1998


  • Content-based image retrieval
  • Image feature extraction/representation
  • Image indexing and searching
  • Parallel implementation and distributed computing
  • Wavelet transform


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