This paper presents an automatic fingerprint classification technique similar to that reported by Ongun and Halici (see Proc. of IEEE vol.84, no.10, p.1497-12, 1996) but, an inverse filtering technique was introduced to restore the distorted parts of the images prior to the feature extraction stage. The results have shown that introducing the inverse filtering stage has improved the percentage of correct classification. Typical classification accuracy reaches 91% with no rejects, 98% with 8.1% rejects compared to the 87% with no rejects, 95% with 9.4% rejects obtained using the previously reported technique