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Fingerprint enhancement proceeds by fully utilizing the intrinsic properties of original images to improve the ridges and eliminate the noises. Although Gabor filter is a classical enhancement method, its function may suffer for the low-quality images due to the unreliable orientation and frequency map estimated by conventional approach. In this paper, a new approach has been proposed to estimate these parameters in an effective way. The local image is modeled as a non-stationary signal and the technique of Short Time Fourier Transform(STFT) is applied to it. Besides, to avoid the multi-step processing and inter-dependency, we extend the theory of probability in mathematics to get the orientation and frequency simultaneously. The performance of our approach is evaluated by the verification system of NIST and FVC2004 DB1_A database. Experimental results show that our method can improve both the image quality and the accuracy of fingerprint recognition.