Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-28
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Content-based image retrieval has recently become an important research topic and has been widely used for managing images from repertories.
In this article, we address an efficient technique, called MNGS, which integrates multiview constrained nonnegative matrix factorization (NMF) and Gaussian mixture model- (GMM-) based spectral clustering for image retrieval.
In the proposed methodology, the multiview NMF scheme provides competitive sparse representations of underlying images through decomposition of a similarity-preserving matrix that is formed by fusing multiple features from different visual aspects.
In particular, the proposed method merges manifold constraints into the standard NMF objective function to impose an orthogonality constraint on the basis matrix and satisfy the structure preservation requirement of the coefficient matrix.
To manipulate the clustering method on sparse representations, this paper has developed a GMM-based spectral clustering method in which the Gaussian components are regrouped in spectral space, which significantly improves the retrieval effectiveness.
In this way, image retrieval of the whole database translates to a nearest-neighbour search in the cluster containing the query image.
Simultaneously, this study investigates the proof of convergence of the objective function and the analysis of the computational complexity.
Experimental results on three standard image datasets reveal the advantages that can be achieved with the proposed retrieval scheme.
American Psychological Association (APA)
Xie, Qunyi& Zhu, Hongqing. 2016. Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1112012
Modern Language Association (MLA)
Xie, Qunyi& Zhu, Hongqing. Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method. Mathematical Problems in Engineering No. 2016 (2016), pp.1-15.
https://search.emarefa.net/detail/BIM-1112012
American Medical Association (AMA)
Xie, Qunyi& Zhu, Hongqing. Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1112012
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112012