Experimental Comparison of Orthogonal Moments as Feature Extraction Methods for Character Recognition

The selection of a good feature extraction technique is very important in any classification problem. Moments, especially orthogonal moments, seem to be a powerful option in the case of digital image compression, description and recognition. Nowadays, there is a considerable amount of orthogonal moments reported in the literature, each one with some advantages and drawbacks. In this paper, we carry out an experimental comparison of several orthogonal moments for the character recognition problem. Firstly, we compare orthogonal moments with other kinds of feature extraction methods and after that, we compare the different orthogonal moments taking into account different evaluation parameters. Experiments were made by using printed and handwritten digit datasets and the well-known measures: precision, recall and accuracy were used to validate the results. This experimental study corroborates the good performance of orthogonal moments. Besides, more specific results obtained in different kinds of experimentations allow coming to conclusions that could be very useful for the community of image recognition practitioners