New method of non-negative matrix factorization combined with Isomap for image retrieval
NMF和Isomap相结合的图像检索新方法*

The Non-negative Matrix Factorization is a local data mining method which can extract the local feature of a image, it can describe the relevant image distribution on the space of base matrix. But NMF neglects the inner geometric structure of data. In this paper a new method which integrates NMF and non-linear dimensionality reduction Isomap is proposed. The global dimensionality reduction method can discover the inner structure and relativity of the data, it makes the high dimension data visualization on lower space In image retrieval experiment, the method can obtain information more precise and improve the accuracy of retrieval.