Biometric Databases
نویسندگان
چکیده
Biometric databases are the set of biometric features collected from a large public domain for the evaluation of biometric systems. For the evaluation of any algorithm for a particular biometric trait, the database should be a large collection of that particular biometric trait. The creation and maintenance of biometric databases involve various steps like enrollment and training. Enrollment is storing the identity of an individual in the biometric system with his/her biometric templates. Every system has some enrollment policy, like the procedure for capturing the biometric samples, quality of the templates. These policies should be made such that they are acceptable to the public. For example, the procedure for capturing iris images involves the use of infrared light, which might even cause damage to human eyes. The signature of any individual is considered private for him, and he might have some objection to giving his signature for enrollment in any such system because of the unpredicted use of their templates (where and how this information may be used). There are two types of enrollment, positive enrollment and negative enrollment. Positive enrollment is for candidates with correct identity civilians while negative enrollment is for unlawful or prohibited people. For enrollment, the biometric sample captured should be such that the algorithms can perform well on that. The features which are required for any algorithm to verify or match the template should be present. The poor biometric sample quality increases the failure to enroll rate. For verification also, if the biometric sample is not captured properly this may lead to an increase in false acceptance and false rejection rates. This increase in failure to enroll and false acceptance and false rejection rates increases the manual intervention for every task, which leads to a further increase in the operational cost along with the risk in security. Training is tuning the system for noise reduction, preprocessing, and extracting the region of interest so as to increase the verification accuracy (decreasing the false acceptance and false rejection rates).
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