Download Introduction to Biometrics by Anil K. Jain PDF
By Anil K. Jain
Biometric popularity, or just biometrics, is the technological know-how of creating the identification of anyone in line with actual or behavioral attributes. it's a quickly evolving box with functions starting from securely gaining access to one’s machine to gaining access right into a nation. whereas the deployment of large-scale biometric structures in either advertisement and executive functions has elevated the general public know-how of this know-how, "Introduction to Biometrics" is the 1st textbook to introduce the basics of Biometrics to undergraduate/graduate scholars. the 3 regular modalities within the biometrics box, specifically, fingerprint, face, and iris are lined intimately during this e-book. Few different modalities like hand geometry, ear, and gait also are mentioned in short besides complicated issues similar to multibiometric platforms and safety of biometric structures. workouts for every bankruptcy may be on hand at the e-book web site to assist scholars achieve a greater knowing of the themes and procure useful event in designing computing device courses for biometric purposes. those are available at: http://www.csee.wvu.edu/~ross/BiometricsTextBook/.
Designed for undergraduate and graduate scholars in machine technological know-how and electric engineering, "Introduction to Biometrics" can be compatible for researchers and biometric and computing device safeguard professionals.
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Additional resources for Introduction to Biometrics
The ear recognition approaches are either based on matching the distance of salient points on the pinna from a landmark location on the ear or based on the appearance of the ear. Ear recognition could be useful for identifying a person based on a proﬁle photograph. See Chapter 5 for more details on ear biometric systems. Voice: Voice is a combination of physical and behavioral biometric characteristics. , vocal tract, mouth, nasal cavities, and lips) that are used in the synthesis of the sound.
Therefore, these users are expected to have low false accept and false reject errors. 2. Goats refer to users who are prone to false rejects. The biometric feature sets of such users typically exhibit large intra-class variations. 3. Lambs are users whose biometric feature set overlaps extensively with those of other individuals. The biometric feature sets of these users have high inter-user similarity. Thus, a randomly chosen user (from the target population) has a higher probability of being accepted as a lamb than as a sheep.
10 Intra-user variations. (a) Variations in the ﬁngerprints of the same person due to difference in position and orientation of the ﬁnger printed, (b) variations in the face images of the same person due to changes in pose, and (c) variations in the iris images due to difference in dilation and gaze direction. 4 Biometric System Errors 17 In a password-based system, a perfect match between two alphanumeric strings is necessary to validate a user’s identity. On the other hand, biometric systems mostly decide on a person’s identity based on a close match between the template and the query, where the strength of the match (or the degree of similarity) is represented by the match score.