The structural approach in the signature verification, representing a signature as a structural form of local primitives, shows an excellent performance since it counts in the local characteristics such as local variation, stroke complexity, and etc. However, this method has a problem of template data sizing which can not fix the number of subpatterns comprising a signature. In this paper, we proposed a new algorithm to reduce the signature data into a fixed size by selecting a fixed number of subpatterns which is considered as important parts. As a result, it shows more excellent performance when the fixed sized sub-patterns is applied with local weights extracted from variational characteristics and complexities in local part. And the number of subpatterns representing a signature reference model can be fixed under a certain number of segments determined appropriately.