Finger Print Enhancement Using Minutiae Based Algorithm?

The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the thinned image. The false matching ratio is better compared to the existing algorithm. This paper describes Minutiae based Fingerprint Verification and Recognition Algorithm for Offline Systems. Reprocessing stage includes Image Enhancement, Binarization, Segmentation, ROI extraction and Thinning. Quality of poor and distorted images is improved by Image Enhancement. Improved images are binarized and segmented to extract Region of Interest (ROI). This image is thinned to extract Minutiae. Feature extraction stage includes the extraction of Minutiae i.e. Ridge Terminations and Ridge Bifurcations. Post processing stage includes removal of False Minutiae and then saving of templates. In matching stage, template generated by test image was matched with the saved one. This algorithm has been tested with FVC- 2004 database and resulted 90 % accuracy with 5% FAR (False Acceptance Ratio) & 2% FRR (False Rejection Ratio).