After discussing each of the key words in this definition, performance measures for a biometric technology are reviewed. The most commonly discussed performance measure of a biometric is its identifying power. How the biometric industry is structured is then briefly addressed, followed by a discussion of fingerprints as a means of identification, with some attention to the use of fingerprint capture devices for credit cards and ATM cards. Other biometric technologies considered in this paper relate to eye patterns (pattern of flecks on the iris and the blood vessel pattern on the back of the eye); hand scans; signature dynamics; voice verification; typing rhythms (keystroke dynamics); and facial features. The latter technology is one of the fastest growing areas of the biometric industry in terms of new development efforts. Many of these efforts use either neural network technology or statistical correlations of the face's geometric shape. Most developers, however, have had difficulty achieving high levels of performance when database sizes increase into the ten's of thousands or higher. Still, interest in this field from government agencies and the financial sector is high.