Khanyile, NPDe Kock, AMathekga, Mmamolatelo E2015-08-192015-08-192014-09Khanyile, N.P, De Kock, A and Mathekga, M.E. 2014. Similarity score computation for minutiae-based fingerprint recognition. In: 2014 IEEE International Joint Conference on Biometrics, Clearwater, FL 29 September - 2 October 2014http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6996286&abstractAccess=no&userType=insthttp://hdl.handle.net/10204/80412014 IEEE International Joint Conference on Biometrics, Clearwater, FL 29 September - 2 October 2014. . Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's websiteThis paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae-based fingerprint matching has been studied extensively in the literature, however, there is still a need for major improvement especially when it comes to comparing partial fingerprints. This paper looks at existing similarity measures; discusses their performance at discriminating between minutiae points from fingerprints of the same finger and of different fingers. The matching problem has been broken down into smaller subproblems which are easier to define and solve. Each of the scores discussed are analyzed and tested to see if they are able to deal with each of the matching subproblems. Results show that most scores in the literature fall in one of two ends of matching; good at discriminating impostor matches, or good at discriminating genuine matches. The authors propose a score which bridges these two types of scores and enables optimal impostor and genuine comparisons.enBiometricsMinutiae pointsFingerprintsSimilarity score computation for minutiae-based fingerprint recognitionConference PresentationKhanyile, N., De Kock, A., & Mathekga, M. E. (2014). Similarity score computation for minutiae-based fingerprint recognition. IEEE. http://hdl.handle.net/10204/8041Khanyile, NP, A De Kock, and Mmamolatelo E Mathekga. "Similarity score computation for minutiae-based fingerprint recognition." (2014): http://hdl.handle.net/10204/8041Khanyile N, De Kock A, Mathekga ME, Similarity score computation for minutiae-based fingerprint recognition; IEEE; 2014. http://hdl.handle.net/10204/8041 .TY - Conference Presentation AU - Khanyile, NP AU - De Kock, A AU - Mathekga, Mmamolatelo E AB - This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae-based fingerprint matching has been studied extensively in the literature, however, there is still a need for major improvement especially when it comes to comparing partial fingerprints. This paper looks at existing similarity measures; discusses their performance at discriminating between minutiae points from fingerprints of the same finger and of different fingers. The matching problem has been broken down into smaller subproblems which are easier to define and solve. Each of the scores discussed are analyzed and tested to see if they are able to deal with each of the matching subproblems. Results show that most scores in the literature fall in one of two ends of matching; good at discriminating impostor matches, or good at discriminating genuine matches. The authors propose a score which bridges these two types of scores and enables optimal impostor and genuine comparisons. DA - 2014-09 DB - ResearchSpace DP - CSIR KW - Biometrics KW - Minutiae points KW - Fingerprints LK - https://researchspace.csir.co.za PY - 2014 T1 - Similarity score computation for minutiae-based fingerprint recognition TI - Similarity score computation for minutiae-based fingerprint recognition UR - http://hdl.handle.net/10204/8041 ER -