Principal component analysis (PCA) is very effective in palmprint recognition. However, with enlargement of the palmprint image library, the training time of the transforming matrix increases rapidly. When new palmprintis added in, the PCA transforming matrix should be retrained, so the cost of adding new palmprint to the libarary increases rapidly with the enlargement of the palmprint image libarary. It has been a major obstacle to the extensive use of PCA that how to make PCA easy to use, meanwhile the recognition performance is maintained. A PCA reconstruction error palmprint recognition method in which the PCA reconstruction error is taken for classification basis is proposed. The proposed method bases on the same theorem with PCA, so it can achieve the same performance with PCA when using the nearest neighbour classifier. The recognition time can be decreased sharply, and it is very easy to enlarge the palmprint image library with proposed method.