A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition system.

 It requires no physical interaction on behalf of the user.  It does not require an expert to interpret the comparison result.  Identify a particular person from large crowd.  Verification of credit card, personal ID, passport.

 Different methods of face recognition.  Feature extraction methods  Holistic methods  Hybrid methods

Every face has at least 80 distinguishable parts called nodal points. Some of them are:

1.Distance between the eyes

Every face has at least 80 distinguishable parts called nodal points. Some of them are: 1.Distance between the eyes 2.Width of the nose

Every face has at least 80 distinguishable parts called nodal points. Some of them are: 1.Distance between the eyes 2.Width of the nose 3.Depth of eye sockets

Every face has at least 80 distinguishable parts called nodal points. Some of them are: 1.Distance between the eyes 2.Width of the nose 3.Depth of eye sockets 4.Structure of cheek bones

Every face has at least 80 distinguishable parts called nodal points. Some of them are: 1.Distance between the eyes 2.Width of the nose 3.Depth of eye sockets 4.Structure of the cheek bones 5.Length of jaw line

A general face recognition software conducts a comparison of these parameters to the images in its database. Depending upon the matches found, it determines the result. This technique is known as feature based matching and it is the most basic method of facial recognition.

The only way to overcome this challenge is better equipment, i.e. basically, use of high tech cameras. It is very much essential for the system to catch the image accurately.

The only way to overcome this challenge is better ALGORITHMS for facial recognitions. If the systems are programmed for every possible permutation and combination of the image, an accurate match can be achieved. Some algorithms that try to overcome this problem are as follows: -Half-face based algorithm -Perturbation Space Method(PSM). -Adaptive Regional Blend Matching(ARBM) Method. -Neural network, etc.

PSM algorithm that converts two dimensional image (e.g. photographs into three – dimensions (such a process is called “Morphing” ). The three – dimensionsional representation of the head are then rotated in Both the left-to-right and up-and down directions.

The facial recognition equipment used for basic surveillance purpose has 3 important components. 1.The camera or scanning device 2.Infrared illuminator 3.An efficient software

An IR-illuminator is a device that emits infrared light-low frequency electromagnetic radiation that's outside the visible spectrum. In other words, it gives off light that a camera can pick up and use, but that a person can't see-so while it's still dark to the human eye, the camera can see just fine. There are 3 main types of infrared illuminators namely diodes, lamps & lasers.

Facial recognition is a very useful mechanism when it comes to office related user identification. One such example is a product of Havon industries called FaceID. Face ID is industry first embedded facial recognition system with leading “Dual Sensor” Facial Recognition Algorithm, which designed for application like physical access control and time attendance, identity management and so on.

In around 10 years from now, it is being estimated that facial recognition technology will be the backbone of all major security, home and networking service. With the growth of social networking over the web, unbelievably accurate facial recognition algorithms and advanced equipment, a person’s face, no mater ageing or disguises or damage, can be recognized and data about that person can be produced. Here is a small glimpse of what facial recognition technology would make of the future social networking….

Assuming amazing resolutions, facial and object recognition, this is how social networking would be in the future….

Pros: 1.Better security systems. 2.Easy user verifications. 3.Greatly reduces current load on security and judicial systems. Cons: 1.Privacy issues. 2.Even helps in kidnapping! 3.Errors in detection may cause inconvenience to innocent users.

Counting of people in a room (e.g. for temperature adjustment) Domestic security systems Police surveillance Domestic Computer / phone identification systems Employee management systems in Companies. National and International security systems.

1. W. Bledsoe. Man-machine facial recognition 2. T. Kanade Computer Recognition of Human Faces