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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.
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.
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:
There are a number of reasons to choose face recognition. This includes the following:
The Face – unique part. For face recognition there are two types of comparisons:
All identification or authentication technologies operate using the following four stages:
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.
The implementation of face recognition technology includes the following three stages:
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.
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.
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.
Face recognition systems can’t tell the difference between identical twins.
The natural use of face recognition technology is the replacement of PIN.
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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