A handwritten Chinese character recognition system using hierarchical displacement extraction based on directional features

A recognition system using displacement extraction based on directional features is proposed for handwritten Chinese characters. In the system, after extracting the features from an input image, the displacement is extracted by the minimization of an energy functional, which consists of the Euclidean distance and the smoothness of the extracted displacement. The coarse-to-fine strategy is adopted to escape local minima and reduce computational costs. The statistical classification is performed based on the estimated variance. In addition, the smoothness of the extracted displacement is utilized. An improvement in recognition performance is achieved as compared with the method without displacement extraction.

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