The purpose of fingerprint image enhancement is to improve the clarity and quality of its local features. The quality of fingerprint image determines the accuracy and reliability of minutia extraction which also determines the accuracy of an automatic fingerprint recognition system. In this paper, we propose an adaptive image pre-processing approach that can significantly improve poor quality images according to their noise level based on contrast stretching, power-law transformation and Gabor filter. The original image smoothing is performed initially by Gaussian filter, and then processed by the proposed adaptive algorithm, and finally the resultant image is filtered by Gabor filter to get the improved binarized image. Experimental results indicate that the proposed approach improves the quality of image and reduces the noise significantly as compared to other fingerprint image preprocessing approaches. Furthermore, the result of Goodness Index (GI) shows that our proposed approach improves the performance by 9% as compared to conventional Gabor filter based approach and is also better than other reported results. Especially, the performance of GI is improved by more than 40% in some poor quality images.