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Chinese Optics Letters

Chinese Optics Letters

| PUBLISHED MONTHLY BY CHINESE LASER PRESS AND DISTRIBUTED BY OSA

  • Vol. 4, Iss. 5 — May. 10, 2006
  • pp: 272–274

Supervised non-negative matrix factorization based latent semantic image indexing

Dong Liang, Jie Yang, and Yuchou Chang  »View Author Affiliations


Chinese Optics Letters, Vol. 4, Issue 5, pp. 272-274 (2006)


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Abstract

A novel latent semantic indexing (LSI) approach for content-based image retrieval is presented in this paper. Firstly, an extension of non-negative matrix factorization (NMF) to supervised initialization is discussed. Then, supervised NMF is used in LSI to find the relationships between low-level features and high-level semantics. The retrieved results are compared with other approaches and a good performance is obtained.

© 2006 Chinese Optics Letters

OCIS Codes
(100.0100) Image processing : Image processing
(100.5010) Image processing : Pattern recognition
(150.0150) Machine vision : Machine vision

Citation
Dong Liang, Jie Yang, and Yuchou Chang, "Supervised non-negative matrix factorization based latent semantic image indexing," Chin. Opt. Lett. 4, 272-274 (2006)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-4-5-272


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References

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  2. W. Xu, X. Liu, and Y. Gong, SIGIR Forum (Toronto, Canada, 2003) p.267.
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