NDLI: A fast image retrieval algorithm with automatically extracted discriminant features

Content Provider	IEEE Xplore Digital Library
Author	Wey-Shiuan Hwang Weng, J.J. Ming Fang Jianzhong Qian
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA (Wey-Shiuan Hwang)
Abstract	Fisher's discriminant analysis is very powerful for classification but it does not perform well when the number of classes is large but the number of samples in each class is small. We propose to resolve this problem by dynamically grouping classes at different levels in a tree. We recast the problem of classification as a regression problem so that the classification (class labels as output) and regression (numerical values as output) are unified. The proposed HDR tree automatically forms clusters in the input space guided by the desired output, which produces discriminant spaces. These discriminant spaces are organized in a coarse-to-fine structure by a tree. A unified size-dependent negative-log-likelihood is proposed to automatically handle both under-sample situations (where the number of samples of each cluster is smaller than the dimensionality of the discriminant space) and the over-sample situations where the HDR tree can reach near-optimal performance. For fast computation, the HDR tree has a logarithmic retrieval time complexity. The proposed HDR tree has been tested with synthetic data, face image databases, and publicly available data sets that use manually selected features.
Starting Page	8
Ending Page	12
File Size	181443
Page Count	5
File Format	PDF
ISBN	076950034X
DOI	10.1109/IVL.1999.781115
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image retrieval Feature extraction Image databases Principal component analysis Linear discriminant analysis Information retrieval Image reconstruction Computer science Power engineering and energy Educational institutions
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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