NDLI: Multiresolution-histogram indexing and relevance feedback learning for image retrieval

Content Provider	IEEE Xplore Digital Library
Author	Muneesawang, P. Ling Guan
Copyright Year	2000
Description	Author affiliation: Dept. of Electr. Eng., Sydney Univ., NSW, Australia (Muneesawang, P.)
Abstract	Two fundamental aspects for content-based image retrieval system are studied: visual feature extraction and retrieval system design. (i) Feature extraction shares some common properties with image compression where the multiresolution nature of wavelet decomposition can be exploited. When wavelet coefficients are vector quantized, the information content in each spatial-frequency subband is mapped onto coding labels. Thus, the statistics of these labels will reflect the subband characteristics of an image. This constitutes a feature vector that is then used for image matching. (ii) The proposed retrieval system supports queries based on system-user interaction that utilise a non-Euclidean similarity measure. A non-linear function based on a radial basis function (RBF) is adopted for characterising the behaviour of human users in an interactive section where relevance feedback is applied. Experimental results show that the retrieval efficiency is considerably improved by implementing the proposed approach.
Starting Page	526
Ending Page	529
File Size	498470
Page Count	4
File Format	PDF
ISBN	0780362977
ISSN	15224880
DOI	10.1109/ICIP.2000.899471
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-10
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Indexing Feedback Image retrieval Spatial resolution Content based retrieval Feature extraction Image coding Wavelet coefficients Statistics
Content Type	Text
Resource Type	Article

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