An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition

In this paper, we present an off-line methodology for isolated Greek handwritten character recognition based on efficient feature extraction followed by a suitable feature vector dimensionality reduction scheme. Extracted features are based on (i) horizontal and vertical zones, (ii) the projections of the character profiles, (Hi) distances from the character boundaries and (iv) profiles from the character edges. The combination of these types of features leads to a 325- dimensional feature vector. At a next step, a dimensionality reduction technique is applied, according to which the dimension of the feature space is lowered down to comprise only the features pertinent to the discrimination of characters into the given set of letters. In this paper, we also present a new Greek handwritten database of 36,960 characters that we created in order to measure the performance of the proposed methodology.