Comparative Study for Color Image Clustering based on Mahalanobis Distance Method

Mahalanobis distance based on fuzzy clustering algorithm for image segmentation

Normalized Clustering Algorithm Based on Mahalanobis Distance

FCM (fuzzy c-means algorithm) based on Euclidean distance function converges to a local minimum of the objective function, which can only be used to detect spherical structural clusters. The added fuzzy covariance matrices in their distance measure were not directly derived from the objective function. In this paper, an improved Normalized Clustering Algorithm Based on Mahalanobis distance by t...

Color Gamut Mapping based on Mahalanobis Distance for Color Reproduction of Electronic Endoscope Image under Different Illuminant

In this paper, a color difference is defined instead of the conventional color differences to evaluate gamut-mapping techniques for electronic endoscope images reproduced on CRT under environmental illuminant. This color difference is defined from Mahalanobis distance by using covariance matrices for differences of metric lightness, chroma and hue angle. The covariance matrices for endoscope im...

Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm

Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to...

New Multi Access Selection Method Based on Mahalanobis Distance

Abstract In next generation wireless communications, the evolution of the mobile terminal towards a multimode architecture, will allow the mobile users to benefit simultaneously from various radio access technologies (RAT’s). The most important issue is how to choose the most appropriate time to start a redirection of traffic flow, and how to choose the most suitable network in terms of quality...