This paper investigates the performance of a handwritten character recognition method by hierarchical displacement extraction based on NIST special database (HSF7). The method is composed of a displacement extraction technique and a coarse-to-fine search strategy. In the displacement extraction technique, the displacement (correspondence) between an input pattern and a prototype is iteratively computed by minimizing a functional defined in the framework of regularization theory. In the coarse-to-fine search strategy, the above-mentioned displacement is determined with multi-resolution images to avoid the pitfalls of local minimum and make the number of iterations low. In addition, a new idea is proposed for reducing the cost of computation without degrading the recognition performance, in which the number of candidate proto-types is eliminated gradually through the hierarchical procedure of the coarse-to-fine search strategy.