Performance evaluation of advanced correlation filters for printed character recognition

Correlation filters have been widely used in several pattern recognition applications. These filters can reliably detect and accurately locate a target with good tolerance to geometrical modifications and the presence of additive and nonoverlapping noise in the scene. This work presents an exhaustive performance evaluation of several advanced correlation filters for the task of printed character recognition. Several printed character strings in the English alphabet containing geometrical modifications and nonuniform illumination conditions are recognized using different advanced correlation filters. The performance of each tested filter is characterized in terms of efficiency of character recognition and accuracy of character location estimation.