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Face Recognition Technology

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Words: 1228 |

Pages: 3|

7 min read

Published: Oct 11, 2018

Words: 1228|Pages: 3|7 min read

Published: Oct 11, 2018

Table of contents

  1. What are biometrics?
  2. Why we choose face recognition over other biometric?
  3. Face recognition
  4. Implementation of face recognition technology
  5. How to face recognition systems work
  6. Face Bunch Graph

The information age is quickly revolutionizing the way transactions are completed. Everyday actions are increasingly being handled electronically, instead of with pencil and paper or face to face. This growth in electronic transactions has resulted in a greater demand for fast and accurate user identification and authentication. Access codes for buildings, banks accounts, and computer systems often use a PIN for identification and security clearances.

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Using the proper PIN gains access, but the user of the PIN is not verified. When credit and ATM cards are lost or stolen, an unauthorized user can often come up with the correct personal codes. Despite the warning, many people continue to choose easily guessed PIN?s and passwords: birthdays, phone numbers and social security numbers. Recent cases of identity theft have heightened the need for methods to prove that someone is truly who he/she claims to be.

Face recognition technology may solve this problem since a face is undeniably connected to its owner expect in the case of identical twins. It's a nontransferable. The system can then compare scans to records stored in a central or local database or even on a smart card.

What are biometrics?

A biometric is a unique, measurable characteristic of a human being that can be used to automatically recognize an individual or verify an individual?s identity. Biometrics can measure both physiological and behavioral characteristics. Physiological biometrics (based on measurements and data derived from direct measurement of a part of the human body) include:

  • Finger-scan
  • Facial Recognition
  • Iris-scan
  • Retina-scan
  • Hand-scan

Why we choose face recognition over other biometric?

There are a number of reasons to choose face recognition. This includes the following:

  • It requires no physical interaction on behalf of the user.
  • It is accurate and allows for high enrolment and verification rates.
  • It does not require an expert to interpret the comparison result.
  • It can use your existing hardware infrastructure, existing cameras and image capture Devices will work with no problems
  • It is the only biometric that allow you to perform passive identification in a one to. Many environments (e.g.: identifying a terrorist in a busy Airport terminal)

Face recognition

The Face – unique part. For face recognition there are two types of comparisons:

  1. Verification. This is where the system compares the given individual with who that individual says they are and gives a yes or no decision.
  2. Identification. This is where the system compares the given individual to all the Other individuals in the database and gives a ranked list of matches.

All identification or authentication technologies operate using the following four stages:

  • Capture: A physical or behavioral sample is captured by the system during Enrollment and also in the identification or verification process b. Extraction: Unique data is extracted from the sample and a template is created.
  • Comparison: The template is then compared with a new sample.
  • Match/ nonmatch: The system decides if the features extracted from the new Samples are a match or a no match d.

Enrollment module: An automated mechanism that scans and captures a digital or an analog image of living personal characteristics. Database: Another entity which handles compression, processing, storage and compression of the captured data with stored data. Identification module: The third interfaces with the application system.

Implementation of face recognition technology

The implementation of face recognition technology includes the following three stages:

  • Data acquisition
  • Input processing
  • Face image classification and decision making

The input can be recorded video of the speaker or a still image. A sample of 1 sec duration consists of a 25 frame video sequence. More than one camera can be used to produce a 3D representation of the face and to protect against the usage of photographs to gain unauthorized access.

A pre-processing module locates the eye position and takes care of the surrounding lighting condition and color variance. First, the presence of faces or face in a scene must be detected. Once the face is detected, it must be localized. ? Some facial recognition approaches use the whole face while others concentrate on facial components and/ or regions (such as lips, eyes etc). The appearance of the face can change considerably during speech and due to facial expressions.

Face image classification and decision making

The synergetic computer is used to classify optical and audio features, respectively. A synergetic computer is a set of an algorithm that simulates synergetic phenomena. In the training phase, the BIOID creates a prototype called face print for each person. A newly recorded pattern is pre-processed and compared with each faceprint stored in the database. As comparisons are made, the system assigns a value to the comparison using a scale of one to ten. If a score is above a predetermined threshold, a match is declared.

How to face recognition systems work

If you look in the mirror, you can see that your face has certain distinguishable landmarks. These are the peaks and valleys that make up the different facial features. Software defines these landmarks as nodal points.

There are about “80 nodal points” on a human face.

Here are few nodal points that are measured by the software.

  • the distance between the eyes
  • width of the nose
  • depth of the eye socket
  • cheekbones
  • jawline
  • chin

Face Bunch Graph

A Face bunch graph is created from “70 nodal points” to obtain a general representation of the face. Given an image, the face is matched to the Face bunch graph to find the same point. These nodal points are measured to create a numerical code, a string of numbers that represents a face in the database. This code is called face print.

Only 14 to 22 nodal points are needed to face it software to complete the recognition process.

Advantages:

  • There are many benefits to face recognition systems such as its convenience and Social Acceptability. All you need is your picture taken for it to work.
  • Face recognition is easy to use and in many cases, it can be performed without a Person even knowing.
  • Face recognition is also one of the most inexpensive biometric in the market and Its price should continue to go down.

Disadvantages:

Face recognition systems can’t tell the difference between identical twins.

The natural use of face recognition technology is the replacement of PIN.

Government Use:

  • Law Enforcement: Minimizing victim trauma verifying Identify for court records, and comparing school surveillance camera images to know child molesters.
  • Security/Counterterrorism: Access control, comparing surveillance images to Know terrorist.
  • Immigration: Rapid progression through Customs.
  • Voter verification: Where eligible politicians are required to verify their identity during a voting process this is intended to stop “proxy? voting where the vote may not go as expected.

Commercial Use:

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  • Residential Security: Alert homeowners of approaching personnel.
  • Banking using ATM: The software is able to quickly verify a customer’s face.
  • Physical access control of buildings areas, doors, cars or net access.

Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipment is going down dramatically due to the integration and the increasing processing power. Certain applications of face recognition technology are now cost-effective, reliable and highly accurate. As a result, there are no technological or financial barriers to stepping from the pilot project to widespread deployment.

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Cite this Essay

Face Recognition Technology. (2018, October 08). GradesFixer. Retrieved May 21, 2024, from https://gradesfixer.com/free-essay-examples/face-recognition-technology/
“Face Recognition Technology.” GradesFixer, 08 Oct. 2018, gradesfixer.com/free-essay-examples/face-recognition-technology/
Face Recognition Technology. [online]. Available at: <https://gradesfixer.com/free-essay-examples/face-recognition-technology/> [Accessed 21 May 2024].
Face Recognition Technology [Internet]. GradesFixer. 2018 Oct 08 [cited 2024 May 21]. Available from: https://gradesfixer.com/free-essay-examples/face-recognition-technology/
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