Browsing by Author "Adewole, Kayode S"
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Item Fuzzy Logic Approach to determine Security Level of Biometrics(IEEE Nigeria Computer Chapter., 2014) Abikoye, Oluwakemi Christiana; Adewole, Kayode S; Salahdeen, N.KOne of the methods that use uniquely identifiable physical or behavioral characteristics to identify individuals is Biometrics. As Biometrics becomes the most promising authentication technology, the world is faced with the challenge of choosing the best among the biometrics traits for their security purposes. In this paper, a model is proposed using fuzzy logic approach to evaluate the Biometrics traits in order to determine their security level. Biometrics characteristics categorized by previous researchers in the field of Biometrics was used as knowledge base. The model developed was simulated using Qtfuzzylite 4.0 (A Fuzzy Logic Control Library in C++) and the results show that Fingerprint, Hand Geometry, Hand Veins, Iris, Ear Canal and Palm print have medium security level among the fifteen (15) Biometrics traits considered based on the following metrics; Universality, Uniqueness, Permanence, Collectability, Performance and Circumvention. The results of this simulation further revealed that fuzzy logic approach provides a simple way of drawing definite conclusions from vague and imprecise informationItem A Review of Algorithms for Fingerprint Image Acquisition, Preprocessing and Minutiae Extraction(Faculty of Physical Sciences, University of Ilorin, Ilorin, Nigeria, 2014) Adewole, Kayode S; Jimoh, Rasheed Gbenga; Abikoye, Oluwakemi ChristianaBiometric recognition distinguishes between individuals using physical, chemical or behavioral attributes of the person. These attributes are called biometric identifiers or traits, and include fingerprint, palmprint, iris, face, voice, signature, gaint, and DNA among others. Fingerprint recognition is one of the oldest and most reliable biometric used for personal identification. Fingerprint has come a long way from tedious manual fingerprint matching. The ancient procedure of matching fingerprints manually was extremely cumbersome and time- consuming and required skilled personnel. In this paper, a review of algorithms for the various stages involved in fingerprint recognition such as fingerprint image acquisition, segmentation, normalization, ridge orientation estimation, ridge frequency, Gabor filtering, binarization, thinning, minutiae extraction, template generation, and template matching is presented. It was established that minutiae features of a person fingerprint truly make fingerprint of individual to be unique.