Fingerprint Image Enhancement

Abstract

With the advancement of human life and techniques surrounding people, there is a huge emphasis on person identification applications, biometrics. Fingerprint recognition is one of the techniques with greater attention. This research develops a Fingerprint enhancement technique based on minutiae matching using Gabor filter. To describe how enhancement can change the minutiae matching [6]. Results show that there is a 40 percent increase in minutiae matching after the enhancement of image is done. A key feature in automatic fingerprint matching is to efficiently and accurately extract the minutiae features from the image. This is only possible if the input fingerprint image is of good quality. So in order to make sure fingerprint verification system works properly, images have to be enhanced or, either the input image should be of good quality. This will allow efficient and accurate feature extraction and matching. Automatic fingerprint recognition system works with the extraction and matching of minutiae features such as ridges and valleys and most importantly ridge features. If these ridge features are not extracted properly then the matching will have error. These errors in the extraction and matching can be removed or say reduced by properly enhancing the ridge features in the image by enhancing the image.