Fingerprint recognition: A study on image enhancement and minutiae extraction

Fingerprints are a great source for identification of individuals. Fingerprint recognition is one of the oldest forms of biometric identification. However obtaining a good fingerprint image is not always easy. So the fingerprint image must be preprocessed before matching. The objective of this project is to present a better and enhanced fingerprint image. We have studied the factors relating to obtaining high performance feature points detection algorithm, such as image quality, segmentation, image enhancement and feature detection. Commonly used features for improving fingerprint image quality are Fourier spectrum energy, Gabor filter energy and local orientation. Accurate segmentation of fingerprint ridges from noisy background is necessary. For efficient enhancement and feature extraction algorithms, the segmented features must be void of any noise. A preprocessing method consisting of field orientation, ridge frequency estimation, Gabor filtering, segmentation and enhancement is performed. The obtained image is applied to a thinning algorithm and subsequent minutiae extraction. The methodology of image preprocessing and minutiae extraction is discussed. The simulations are performed in the MATLAB environment to evaluate the performance of the implemented algorithms. Results and observations of the fingerprint images are presented at the end