In order to improve performance, image preprocessing for enhancement is essential in a fingerprint recognition system. Most prominent fingerprint enhancement methods perform well for relatively high-quality images but less effectively for low-quality images, especially where the ridge patterns are very noisy and corrupt. To enhance such images, this paper proposes an effective three-step algorithm, a method that locally normalizes input images, computes the local ridge orientation, and then applies a local ridge compensation filter with a rotated window in order to enhance the ridges by matching the local ridge orientation. Experimental results indicate that the proposed method performs better when compared to some noted methods of enhancing low-quality images.