In online character recognition based on elastic matching, such as dynamic programming matching, many of mis-recognitions are often caused by overfitting, which is the phenomenon that the distance between reference pattern of an incorrect category and an input pattern is under-estimated by unnatural matching. In this paper, a new recognition technique is proposed where category-specific deformations, called eigen-deformations, are utilized to suppress those misrecognitions. Generally, matching results at overfitting are not consistent with the eigen-deformations. Thus, the overfitting can be detected and penalized by a posterior evaluation of this inconsistency. The result of a recognition experiment showed the usefulness of the proposed technique.