On hierarchical content-based image retrieval by dynamic indexing and guided search

Jia You, Qin Li, Jinghua Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review


This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing. It also provides an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features. Experimental results confirm that the new approach is feasible for content-based image retrieval.
Original languageEnglish
Pages (from-to)18-36
Number of pages19
JournalInternational Journal of Cognitive Informatics and Natural Intelligence
Issue number4
Publication statusPublished - 1 Oct 2010


  • Content-based image retrieval
  • Data mining
  • Image classification
  • Image data warehouse
  • Image indexing
  • Similarity measures
  • Wavelet transform

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Artificial Intelligence


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