Abstract: Databases of human dorsal hand vein (DHV) images are created and distributed for the purpose of testing DHV identification algorithm. For logistical and privacy reasons, these databases are often too small to fulfill their potential applications. A novel synthesis method of creating new DHV images using principal component analysis (PCA) is proposed, which can be applied to enlarge the existing DHV image database. Firstly, the origin database is divided into set B and set M. Set B provides a feature space and the set M constitutes a sample space used for projection. Then, the projection coefficients are obtained by projecting the sample space to the feature space. Finally, based on the method of PCA, new data are synthesized using the feature space and the projection coefficients extracted from the existing real data. Dynamic changing of the samples in the two sets can synthesize more and more new samples. The number of the samples in the two sets is also decided by our experiments. Therefore, a new synthesized DHV image database containing 8007 subjects is built in our research with 94 original subjects. The experimental results show that the synthesized database reaches a satisfied recognition rate of 97.84%, which indicates the proposed method performs well and would be applicable in the simulation test.