Non Negative Matrix Factorization Clustering Capabilities; Application on Multivariate Image Segmentation
The clustering capabilities of the Non Negative MatrixFactorization algorithm is studied. The basis images are consideredlike the data membership degree to a particular class.A hard clustering algorithm is easily derived based on theseimages. This algorithm is applied on a multivariate image toperfo...
Main Authors: | Cosmin Lazar, Danielle Nuzillard, Patrice Billaudel, Sorin Curila |
---|---|
Format: | Article |
Language: | English |
Published: |
Editura Universităţii din Oradea
2009-10-01
|
Series: | Journal of Electrical and Electronics Engineering |
Subjects: | |
Online Access: | http://electroinf.uoradea.ro/reviste%20CSCS/documente/JEEE_2009/Articole_pdf_JEEE_EL_nr_2/JEEE_2009_Nr_2_EL_Lazar_NonNegative.pdf |
Similar Items
-
Statistical Images Segmentation
by: Corina Curilă, et al.
Published: (2008-05-01) -
Segment Congruence Analysis: An Information Theoretic Approach
by: Hosseini-Chaleshtari, Jamshid
Published: (1987) -
Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization
by: Nicolas Sauwen, et al.
Published: (2017-05-01) -
On Capability Indices for Multivariate Autocorrelated Processes
by: Sueli Aparecida Mingoti, et al.
Published: (2011-12-01) -
Regions Matching Algorithms Analysis to Quantify the Image Segmentation Results
by: Oleh BEREZSKY, et al.
Published: (2017-01-01)