Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The clustering capabilities of the Non Negative Matrix Factorization algorithm is studied. The basis images are considered like the membership degree of the data to a particular class. A hard clustering algorithm is easily derived based on these images. This algorithm is applied on a multivariate image to perform image segmentation. The results are compared with those obtained by Fuzzy K-means algorithm and better clustering performances are found for NMF based clustering.  also show that NMF performs ll when  deal with uncorrelated clusters but it cannot distinguish correlated clusters. This is an important drawback when  try to use NMF to perform data clustering.
['Cosmin Lazar', 'Andrei Doncescu']
I am writing a research paper on a idea Non Negative Matrix Factorization Clustering Capabilities; Application on Multivariate Image Segmentation
[{"from": "human", "value": "I am writing a research paper on a idea Non Negative Matrix Factorization Clustering Capabilities; Application on Multivariate Image Segmentation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The clustering capabilities of the Non Negative Matrix Factorization algorithm is studied. The basis images are considered like the membership degree of the data to a particular class. A hard clustering algorithm is easily derived based on these images. This algorithm is applied on a multivariate image to perform image segmentation. The results are compared with those obtained by Fuzzy K-means algorithm and better clustering performances are found for NMF based clustering.  also show that NMF performs ll when  deal with uncorrelated clusters but it cannot distinguish correlated clusters. This is an important drawback when  try to use NMF to perform data clustering."}]