Alexander Denecke, Heiko Wersing, Jochen Steil, Edgar Körner, "Robust object segmentation by adaptive metrics in Generalized LVQ", Proceedings of the European Symposium on Artificial Neural Networks (ESANN), pp. 319–324, 2008.

We investigate the effect of several adaptive metrics in the context of figure-ground segregation, using Generalized LVQ to train a classifier for image regions. Extending the Euclidean metrics towards local matrices of relevance-factors does not only lead to a higher classification accuracy and increased robustness on heterogeneous/noisy data, but also figureground segregation using this adaptive metrics enables a considerably higher recognition performance on segmented objects of real image data.