AN ASSESSMENT OF FINGERPRINT AUTHENTICATION SYSTEM FOR ATM SECURITY
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Background of the Study
A biometric system is, in essence, a pattern recognition system that functions by first gathering biometric data from a person, then extracting a feature vector from the collected data, and then comparing the extracted feature vector with the feature vector stored in the database. Authentication of people has been an alluring target for computer vision research from the beginning. Authentication systems that are known as biometrics systems are those that are based on human traits such as the face, finger, iris, and voice (Adesanya , 2022). The gathering of the input picture and the generation of significant feature vectors, such as color and texture, are the fundamental building blocks of any biometric system.
Authenticating the identification of a live person based on physiological or behavioral features is made possible with the widespread and reliable use of biometric recognition technology today. One example of a physiological characteristic is a reasonably constant physical trait, such as a person's fingerprint, iris pattern, facial feature, hand profile, or any of a number of other examples. This kind of measurement is essentially static and cannot be altered in substantial ways without strong pressure (Annan, 2020). A person's behavioral characteristics are more of a representation of their psychological make-up than things like their signature, their speaking rhythm, or how quickly they write on a keyboard.
The degree to which individuals differ from one another in terms of their behaviors is greater than the degree to which individuals differ in terms of their physical characteristics. For instance, a person's signature may be impacted by both controlled acts and less psychological aspects, and a person's speech style can be influenced by the present emotional state, while a fingerprint template does not rely on the person's emotional state (Bernard, 2022). In spite of this, none of the physiology-based biometrics provide sufficient recognition rates (also referred to as false acceptance and/or false reject rates, respectively). When we take into consideration that the possibility of discovering two persons with the same iris pattern is nearly nil, it is believed that the automated personal identification verification systems that are based on iris recognition are the most trustworthy (Camillus, 2022). Iris recognition technology is becoming an essential biometric solution for the identification of persons in access control as well as networked access to computer applications because of this reason. In contrast to the fingerprint, the iris is hidden from view behind the cornea and the eyelid, where it is shielded from the elements. The minute radial characteristics of the iris do not experience the degenerative changes associated with aging, and they maintain their stable and fixed appearance from around one year of age throughout life (Chibuzo , 2021).
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