Fingerprint Enhancement for Minutiae Matching

Fingerprint is a biometric that provides secure method to authenticate a person due to its permanent feature and uniqueness that remain throughout human life. It has been in used for more than 100 years as a result of its feasibility, accuracy, reliability, and acceptability. Although there exist many algorithms for fingerprint authentication, there is still a need to close the gap of accurateness. Among the algorithm fingerprint methods are minutiae matching and pattern matching method. A minutiae matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper the minutiae extraction method was improved by combining it with image enhancement that includes noise reduction, smoothing, contrast stretching, histogram equalization, Fourier transform and edge enhancement. This method presented a reasonable performance that gives a recognition rate up to 96.7% accuracy under supervised training fingerprint images.