Chinese Optics Letters, 2006, 4 (5): 05272, Published Online: Jun. 6, 2006
Supervised non-negative matrix factorization based latent semantic image indexing
100.0100 Image processing 100.5010 Pattern recognition and feature extraction 150.0150 Machine vision
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.
Dong Liang, Jie Yang, Yuchou Chang. Supervised non-negative matrix factorization based latent semantic image indexing[J]. Chinese Optics Letters, 2006, 4(5): 05272.
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