Features of Facial Recognition Systems.

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Commercial Security

Imaging Analysis is arguably one of the fastest growing sectors of the Surveillance market place. It is gaining a strong foothold within Commercial Security considerations. In Shopping Centers, Public Buildings, Campuses and even Commercial premises there is an increasing requirement to secure common areas to a reasonable level. Today, we see an overwhelming desire to install a greater number of CCTV cameras, but who monitors each of these cameras and how is one security guard able to identify the threat; a stalker, a murderer or a thief? This is where imaging analysis can assist in a series of measures to ensure that public places are thoroughly scanned and a strict vigil is in place to track the movement of unidentified persons.

Face Recognition Method

With advancement in image analysis, facial recognition system is rapidly gaining its significance. The greater the ability to match a series of points (dimensions & pixel points) on a face, the better the percentage success rate in face identification.

Face Recognition

Humans use faces to recognize individuals. Recent advances in computing technology and capability now enable similar recognition automatically. Early face recognition algorithms used simple geometric models, but the recognition process has now matured into a science of sophisticated mathematical representations and matching processes. Major developments have propelled face recognition technology into the spotlight. Face recognition can be used for both verification (1:1) and Identification (1: N) applications.

Face Template

The heart of the facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a "template" as a unique numerical id for that face. Once the system has stored a "template" it can compare it to the thousands or millions of "templates" stored in a database; each template occupies only 2-3 KB of data.

Algorithm

The right algorithm will enable fast and accurate face localization for reliable detection of multiple faces in still images as well as in live video streams. This simultaneous multiple face processing and identification can happen in a single frame. The face needs to be detected in less than 0.1 seconds and then processed in less than 0.2 seconds. This rapid detection rate allows comparison of up to 100,000 faces per second, through the recorded frames generating the collection of the generalized face features from several images of the same subject and writing it to the database. In this way the enrolled feature templates are more reliable and the face recognition quality increases considerably over time.

Identification vs. Verification

Verification (1:1, one-to-one) – This is the process of determining a person's identity by performing matches against one biometric template that is located upon a known ID. 1:1 verification usually uses a manual interface like a card, RFID, code or any other similar key based indexing.
Identification (1:N, one-to-many) – This is the process of determining a person's identity by performing matches against multiple biometric templates. The identification system is designed to determine identity based solely on biometric information. There are two types of identification systems: positive identification and negative identification. Advanced applications allow our customers full control over recognition methods where we support both 1:1 (verification) and 1: N (identification) methods.

Product Solutions

We offer a range of Facial Recognition Solutions designed to provide verification (1:1) and identification (1: N). These start with the basic Logon system that monitors who is using your computer or laptop. Supervision is a solution for remote facial recognition through Web / 3rd Generation (3G) Cellulars and TCP/IP networks. This allows both local and remote recognition through fast and smart facial recognition engine. Access II and III provide access control support for verification and then combine with Vistrack as a Visitor Tracking system. We also provide identification solutions integrating Logon, Supervisor, Access and Vistrack into our Suspect and Observer packages. FRS Suspect and FRS Observer are advanced surveillance systems that can automatically detect faces both online or offline using the above fast acquisition methods. They analyze the inputs from numerous CCTV cameras, comparing the extracted face templates from the cameras with a database containing previously stored profiles and face templates. As each image is detected they automatically raise alarms through whatever interface is required including SMS, PDA, Email and Web.

Conclusion

Face Recognition Technology will be considered an inevitable part of the Public and Commercial Security Solutions. Through the integration of different biometric tools many industries and organizations will enhance their security situations to a higher level. Image analyzing systems will be extensively used in controlling access, time and attendance management, Management information systems etc. to provide a comprehensive measure to improve safe and peaceful working environment.

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