NDLI: Relevance feedback techniques for image retrieval using multiple attributes

Content Provider	IEEE Xplore Digital Library
Author	Tat-Seng Chua Chun-Xin Chu Kankanhalli, M.
Copyright Year	1999
Description	Author affiliation: Sch. of Comput., Nat. Univ. of Singapore, Singapore (Tat-Seng Chua)
Abstract	The paper proposes a relevance feedback (RF) approach to content based image retrieval using multiple attributes. The proposed approach has been applied to images' text and color attributes. In order to ensure that meaningful features are extracted, a pseudo object model based on color coherence vector has been adopted to model color content. The RF approach employs techniques developed in the fields of information retrieval and machine learning to extract pertinent features from each of the attributes. It then uses the user's relevance judgments to estimate the importance of different attributes in an integrated content based image retrieval. The system developed has been tested on a large image collection containing over 12000 images. The results demonstrate that the proposed RF approaches and pseudo object based color model are effective.
Starting Page	890
Ending Page	894
File Size	504086
Page Count	5
File Format	PDF
ISBN	0769502539
DOI	10.1109/MMCS.1999.779320
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-07
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feedback Image retrieval Radio frequency Content based retrieval Feature extraction Data mining Coherence Information retrieval Machine learning System testing
Content Type	Text
Resource Type	Article

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