Behaviour-based clustering of neural networks applied to document enhancement

Abstract

This work proposes an agglomerative hierarchical clustering algorithm where the items to be clustered are supervised-learning classifiers. The measure of similarity to compare classifiers is based on their behaviour. This clustering algorithm has been applied to document enhancement: A set of neural filters is trained with multilayer perceptrons for different types of noise and then clustered into groups to obtain a reduced set of neural clustered filters. In order to automatically determine which clustered filter is the most suitable to clean and enhance a real noisy image, an image classifier is also trained using multilayer perceptrons. © Springer-Verlag Berlin Heidelberg 2007.