In this paper, a simple technique is proposed for fingerprint analysis using minutiae extraction process with the combination of several techniques for image pre-processing to improve the input image until it is suitable for minutiae extraction. In addition, two major categories of minutiae and bifurcation are used here. | ISSN:2249-5789 S Sai Kumar et al , International Journal of Computer Science & Communication Networks,Vol 2(4), 478-486 Fingerprint Minutia Match Using Bifurcation Technique 1, 2, 3, 4, 5, L. Ravi Kumar1, S. Sai Kumar2, J. Rajendra Prasad 3, B. V. Subba Rao4, P. Ravi Prakash5 Department of Information Technology, Siddhartha Institute of Technology,vijayawada 1 Abstract A fingerprint is believed to be unique to each person and each finger. Fingerprints are one of the most full-grown biometric technologies and are used as proofs of evidence. A fingerprint consists of various types of minutiae and it is one of the most popular categories used in the fingerprint verification system. In this paper, a simple technique is proposed for fingerprint analysis using minutiae extraction process with the combination of several techniques for image pre-processing to improve the input image until it is suitable for minutiae extraction. In addition, two major categories of minutiae and bifurcation are used here. bifurcation, which is the point on the ridge from which two branches derive. Keywords—Bifurcation, Biometrics, Fingerprint, Minutiae, Termination, Thinning. In addition, different from the manual approach for fingerprint recognition by experts, the fingerprint recognition here is referred as AFRS (Automatic Fingerprint Recognition System), which is programbased. 1. Introduction A fingerprint is the feature pattern of one finger. It is believed with strong evidences that each fingerprint is unique. Each person has his own fingerprints with the permanent uniqueness. So fingerprints have being used for identification and forensic investigation for a long time. A fingerprint is composed of many ridges and furrows. These ridges and furrows present good similarities in each small local window, like parallelism and average width. However, shown by intensive research on fingerprint recognition, fingerprints are .
