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Adaptive and Faster Approach to Fingerprint Minutiae Extraction and Validation
Iwasokun gabriel Babatunde, Akinyokun, Oluwole Charles, Alese Boniface kayode, Olabode Olatunbosun
Pages - 414 - 424     |    Revised - 01-09-2011     |    Published - 05-10-2011
Volume - 5   Issue - 4    |    Publication Date - September / October 2011  Table of Contents
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KEYWORDS
AFIS, Pattern Recognition, Pattern Matching, Fingerprint, Post-Processing Algorithm, Crossing Number
ABSTRACT
Fingerprint has remained a very vital index in the field of security where series of Automatic Fingerprint Identification System (AFIS) have been developed for human identification. Many of these systems involve matching each of the features of a template image with each of the features in the feature sets in the reference database to determine the level of match between the template and the reference images. Matching is done on the basis of preset parameters such as feature type, location, orientation and so on. Obtaining the features from the template image and for building a reference database involves the implementation of a sound fingerprint feature detection and extraction algorithm. In this paper, the process of detecting and extracting false and valid features contained in a fingerprint image is discussed. Some of the existing fingerprint features extraction algorithms were firstly modified and the resulting algorithms were implemented. The implementation was carried out in an environment characterized by Window Vista Home Basic as platform and Matrix Laboratory (MatLab) as frontend engine. Fingerprints images of different qualities obtained from the manual (ink and paper) and electronic (fingerprint scanner) methods were used to test the adequacy of the resulting algorithms. The results obtained show that only valid and true minutiae points were extracted from the images.
CITED BY (31)  
1 Iwasokun, G. B., & Akinyokun, O. C. Singular-minutiae points relationship-based approach to fingerprint matching.
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12 Iwasokun, G. B., & Ojo, S. O. (2014). Review and Evaluation of Fingerprint Singular Point Detection Algorithms. British Journal of Applied Science & Technology, 4(35), 4918.
13 Iwasokun, G. B., & Akinyokun, O. C. False Minutiae’Impact on Fingerprint Matching.
14 Babatunde, I. G., Charles, A. O., & Olusegun, O. S. (2014). An Investigation into the Impact of False Minutiae Points on Fingerprint Matching. International Journal of Database Theory and Application, 7(3), 159-178.
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23 Babatunde, I. G., Charles, A. O., & Olatunbosun, O. (2013). Uniformity Level Approach to Fingerprint Ridge Frequency Estimation. International Journal of Computer Applications, 62(22).
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27 Babatunde, I. G., Charles, A. O., & Olatubosun, O. (2012). A Block Processing Approach to Fingerprint Ridge-Orientation Estimation. Computer Technology and Application, 3(6).
28 Iwasokun, G. B., Akinyokun, O. C., & Dehinbo, O. J. Minutiae Inter-Distance Measure for Fingerprint Matching.
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Mr. Iwasokun gabriel Babatunde
Federal University of Technology - Nigeria
maxtunde@yahoo.com
Mr. Akinyokun, Oluwole Charles
- Nigeria
Dr. Alese Boniface kayode
Federal University of Technology, Akure - Nigeria
Dr. Olabode Olatunbosun
Federal University of Technology, Akure - Nigeria