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In this paper, we present a new unsupervised colour image segmentation algorithm using competitive and morphological concepts. The algorithm is carried out in three processing stages. It starts by an estimation of the density function, followed by a training competitve neural network with a new criterion of resemblance called Mahalanobis distance which detects local maxima of the density function,...
In this paper, we present a new neural and statistical classification approach. This procedure uses the neural network with competitive training to detect the local maxima of the probabilities density function's (pdf) which are considered as the prototype of the classes in the data distribution. In order to take account of different forms of distributions; Gaussian and non-Gaussian, we used as criteria...
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