The document discusses biometric technologies and applications. Biometrics refers to technologies that measure physiological or behavioral characteristics to identify or verify individuals. These characteristics include fingerprints, iris scans, facial recognition, gait, and signatures. Contemporary systems use multiple biometrics to increase reliability. Synthetic biometrics can also be generated to improve existing identification systems or for training. However, synthetic biometrics raise ethical issues around forgery and privacy.

1. Biometric Technologies and
Applications
The term “biometric” comes from the Greek words bio (life) and metric
(measurement). However, in its general use, biometric refers to technologies for
measuring and analysing the physiological or behavioural characteristics of a person.
These features are unique to individuals and can therefore be used for verifying or
identifying a person.
The essential biometric properties include:
1. Universal (common characteristics of every individual)
2. Unique (no similarity between two persons in terms of that feature)
3. Permanent (characteristic that will never change with time)
4. Collectable (quantitatively measurable)
5. Reliable (safe and can be operated at an acceptable performance level)
6. Acceptable (socially tolerable and non-invasive)
7. Non-circumventable (how easily the system is fooled in providing impostors
with access)
Biometric technologies try to generate computer models of human physical and
behavioural characteristics in order to reliably identify people. Biometric technologies
are generally considered to be the implementation of pattern recognition algorithms
because they are intended to identify people.
1. Direct Biometrics
The term biometrics refers to the traditional methods of human recognition. The latest
development and application of biometric technologies depend largely on the basic

2. definition of matching patterns that require learning (analysis) and recognition
(synthesis).
1.1 Multimodal Biometrics
Contemporary biometric systems measure multiple physiological or behavioural
characteristics to increase overall reliability. The most commonly used multi-
biometric data in biometric systems include iris and retina, fingerprint, face, ear, and
also geometry and palm-print of the hand.
1.1.1 Fingerprints: It is the most developed biometric sensors and popularly
utilized in forensic investigation.
1.1.2 Signature: Improved human-computer interaction devices enable
handwriting and signatures to be entered and analysed.
1.1.3 Iris & Retina: The system of iris recognition scans the iris surface to
match patterns. Retina recognition systems scan the retina surface and
compare blood vessels, nerve patterns, and other characteristics.
1.1.4 Faces: Face recognition system detects shapes, patterns, and shadows
in the face, extract features and recognize the face identity. It
encompasses all kinds of facial processing, such as tracking, detection,
analysis, and synthesis.
1.1.5 Gait Biometrics: Gait recognition identifies an individual’s walking
pattern. A distinctive advantage of this system is that it offers the
potential for distant or low resolution recognition when other
biometrics may not be perceived.
2. Inverse Biometrics:
Synthetic biometrics provides solutions for improving the reliability of biometric
systems. Synthetic biometric data can improve the efficiency of existing identification
system, improve the robustness of the system, and improve the efficiency of training
system.
2.1 Synthetic fingerprints
2.2 Synthetic signatures
2.3 Synthetic iris & images
2.4 Synthetic faces
3. Ethical Issues of Synthetic Biometrics
Inverse biometrics has several ethical and social aspects including prevention of
undesirable side effects, targeting areas of social concern in biometrics, generating
several copies of original information, threats of forgery etc.
Brainware University