In combination with Wavelet Transform(WT),Two-dimensional Principal Component Analysis(2DPCA) and Ellipsoidal Basis Function(EBF),a fingerprint recognition algorithm based on WT,2DPCA and EBF neural network(EBFNN) is proposed.Original images are decomposed into high-frequency and low-frequency components with WT,and horizontal and vertical high-frequency components are ignored,so the prime features of original images can be obtained;then,the projected features are solved by 2DPCA;finally,fingerprint recognition can be realized by EBFNN.The algorithm combines the optimization of 2DPCA and the adaptability of EBFNN and achieves the accurate recognition rate of 91.4%.The experimental results based on FVC2000 verify that proposed algorithm has higher recognition rate than that of WT-PNN and WT-2DPCA-RBF.