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Biometric System Architecture

Last Updated : 02 Dec, 2022
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Biometrics are computerized methods of identifying a person based on physiological and observable qualities. The use of biometric systems has impacted the way we identify and authenticate ourselves around the world.  By utilizing this technology, not only has the identification of people changed, but also the time it takes to identify and verify people has been significantly reduced. Face, fingerprints, handwriting, palmprints, hand geometry, gait, iris, retinal, and voice are the various characteristics that are measured in biometric techniques. 

Phases of Biometric System

There are two phases of a Biometric System: 

1. Enrollment phase: 
In the enrollment phase, biometric information of the user or person is recorded in a database. It is a one-time process. Generally, in this phase, measurement of the appropriate information is done very precisely. 

2. Recognition phase: 
This is the second phase of the biometric system. This occurs when the detection part begins based on the first phase of the authentication of the user. This phase must be quick, accurate, and able to determine the authentication problem easily.

Biometric System Architecture

Biometric system architecture has the following main components: 

Biometric Architecture

Biometric Architecture

1. Sensor: The sensor is the first block of the biometric system which collects all the important data for biometrics. It is the interface between the system and the real world. Typically, it is an image acquisition system, but it depends on the features or characteristics required that it has to be replaced or not.

2. Pre-processing: It is the second block that executes all the pre-processing. Its function is to enhance the input and to eliminate artifacts from the sensor, background noise, etc. It performs some kind of normalization.

3. Feature extractor: This is the third and the most important step in the biometric system. Extraction of features is to be done to identify them at a later stage. The goal of a feature extractor is to characterize an object to be recognized by measurements.

4. Template generator: The template generator generates the templates that are used for authentication with the help of the extracted features. A template is a vector of numbers or an image with distinct tracts. Characteristics obtained from the source groups come together to form a template. Templates are being stored in the database for comparison and serve as input for the match.

5. Matcher: The matching phase is performed by the use of a match. In this part, the procured template is given to a matcher that compares it with the stored templates using various algorithms such as Hamming distance, etc. After matching the inputs, the results will be generated.

6. Application device: It is a device that uses the results of a biometric system. The Iris recognition system and facial recognition system are some common examples of application devices.

Types of Biometric System

A person’s biometric traits fall into the following three categories: 

  1. Biological
  2. Physiological
  3. Behavioral.

A physiological trait is a biological pattern found on or in the human body, such as a face, fingerprints, iris pattern, DNA, hand geometry, etc. Behavioral patterns, however, develop over time and become consistent characteristics, such as handwriting, voice, gait, and typing rhythm. The biometric feature that is used to identify an individual determines the type of biometric system. Biological characteristics and behavioral traits of individuals can be detected and from which distinct, repeatable biometric features can be extracted to automate recognition.

The types of biometric systems are:

  1. Fingerprint Recognition System
  2. Facial Recognition System
  3. Iris Recognition System
  4. Handwriting Recognition System
  5. Hand geometry Recognition System
  6. Retina Recognition System
  7. Gait Recognition System
  8. Lip Motion Recognition System

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