Genetic Programming with Histograms for Handwritten Recognition

Handwritten recognition is a popular problem which requires special Artificial Intelligent techniques for solving it. In this paper we use Genetic Programming (GP) for addressing the off-line variant of the handwritten digit recognition. We propose a new type of input representation for GP: histograms. This kind of representation is very simple and can be adapted very easily for the GP requirements. Several numerical experiments with GP are performed by using several large datasets taken from the well-known MNIST benchmarking set. Numerical experiments show that GP performs very well for the considered test problems.