Fingerprint segmentation has been considered as one of the critical processes of the automatic fingerprint identification system. Following the analysis of the relationship between the second order statistical characteristics and the grey-scale level, the offset value and the relative direction, an innovative fingerprint segmentation algorithm based on the gray level co-occurrence matrix (GLCM) is thus presented. Firstly, the fingerprint is split into a number of rectangular blocks to get the contrasts of GLCM for each in different directions. And then, to judge for whether a rectangular block is the prospect region or not, the proposed algorithm compares its variance of the contrast with the predefined threshold. The theoretical analysis and experiment results on the FVC2004 show that the proposed algorithm performs well and is robust in handling the varied qualities of fingerprint images collected in any circumstance.