  A classification algorithm that combines the components of k-nearest
neighbours and multilayer neural networks has been designed and tested. With
this method the computational time required for training the dataset has been
reduced substancially. Gabor filters were used for the feature extraction to
ensure a better performance. This algorithm is tested with MNIST dataset and it
will be integrated as a module in the object recognition software which is
currently under development.
