A lot of feature-based correspondence matching methods have been proposed in the field of computer vision, image processing and pattern recognition. These methods are also effective for biometric recognition. In general, in the case of feature-based matching methods, the matching score is calculated as a ratio between the number of feature points and corresponding points. These methods need to normalize image deformation by fitting an image transformation model to images according to the correspondence between images. Then, the matching score is calculated from the normalized images so as to take into consideration image deformation. On the other hand, this paper proposes a score calculation method which calculates a matching score from positional information of corresponding point pairs. The proposed method does not need any deformation model defined for each biometric trait to handle image deformation. The combination of the matching scores defined by the number of corresponding points and the positional information improves the performance of biometric recognition algorithms, since these scores play a complementary role in decision. Through a set of experiments using a palmprint image database, we demonstrate that the proposed method exhibits efficient performance for biometric recognition.