Singularities Detection by Cellular Neural Networks

R. Montufar-Chaveznava (Mexico)


Cellular Neural Networks, Singularities Detection, ImageProcessing.


Singularities detection can be carried out finding the local maxima of the wavelet transform. Wavelet local maxima characterize local shapes of irregular structures in an image. In the other hand, a cellular neural network (CNN) is described as an analog parallel-computing paradigm defined in space, and characterized by the local connections between their processing elements (cells). The CNN principal property is their ability to perform massive processing, characteristic that is very well adapted to some image processing tasks. The mathematical representation of a CNN can be adequate to certain particular representations, such as the wavelet transform. In this work we present a singularities detector based in the wavelet transform implemented in a CNN.

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