Voronoi Pyramids Controlled by Hopfield Neural Networks

We present a novel method for irregular pyramid construction. The contributions of this paper are twofold: (1) Instead of starting with the original regular pixel grid, we first apply an adaptive Voronoi tessellation to the image. This provides the advantage that the number of cells at the bottom level of the pyramid is already reduced as compared to the number of pixels of the original image. (2) For the construction of the irregular pyramid, we present a Hopfield neural network which controls the decimation process. The decimation by Hopfield networks includes naturally the concept of the adaptive pyramid. The validity of our approach is demonstrated by several examples in image segmentation.

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