Orientation field estimation is an essential preprocessing step and it is crucial for the efficiency of the fingerprint recognition algorithm. In this paper

we propose a Grid-Interpolation Model. It partitions the fingerprint plane around singular points with discrete grids

and builds the nonlinear relationship between orientation field and singular points. The orientation of grid points is adjusted by global information of the fingerprint

which is much different from the conventional method. Two experiments are carried out on FVC2002 and FVC2004 databases and the results indicate that the proposed model can reduce noise more efficiently and has more robust performance than the conventional method. Especially as for fingerprints with bad quality

it also can give satisfactory estimation.