Biometric Technologies and Its 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 analyzing the physiological or behavioral 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:
- Universal (common characteristics of every individual)
- Unique (no similarity between two persons in terms of that feature)
- Permanent (characteristic that will never change with time)
- Collectable (quantitatively measurable)
- Reliable (safe and can be operated at an acceptable performance level)
- Acceptable (socially tolerable and non-invasive)
- 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.
- 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 definition of matching patterns that require learning (analysis) and recognition (synthesis).
- 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.
- Fingerprints: It is the most developed biometric sensors and popularly utilized in forensic investigation.
- Signature: Improved human-computer interaction devices enable handwriting and signatures to be entered and analysed.
- 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.
- 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.
- 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.
- 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.
- Synthetic fingerprints
- Synthetic signatures
- Synthetic iris & images
- Synthetic faces
- 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.