Abstract high accuracy and low intrusiveness. It

AbstractThe reason ofthat project is to implement a face recognition algorithm that is presentedhere is a memory based face recognition system. Face recognition challengingdue to the Wide variety of faces and the complexity of noises and imagebackgrounds. And the more familiar functionality of visual surveillancesystems.

The goal of this project is to give a small background about face recognitionand how it works. I also show how humans going to use face recognition in thefuture.  IntroductionAs one of themost successful applications of image analysis and understanding, facerecognition has recently received significant attention, especially during thefew years.

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The strong need for user-friendly systems that can secure our assetsand protect our privacy without losing our identity in a sea of numbers isobvious. At present, one needs a PIN to get cash from an ATM, a password for acomputer, a dozen others to access the internet. Although extremely reliablemethods of biometric personal identification exist. Face recognition is one ofthe few biometric methods that possess the merits of both high accuracy and lowintrusiveness.

It has the accuracy of a physiological approach without beingintrusive. For this reason, since the early 70’s (Kelly, 1970), face recognitionhas drawn the attention of researchers in fields from security, psychology, andimage processing, to computer vision. Numerous algorithms have been proposedfor face recognition; for detailed survey please see Chellappa (1995) and Zhang(1997). Biometricsis the emerging area of bioengineering; it is the automated method ofrecognizing person based on a physiological or behavioral characteristic. Thereexist several biometric systems such as signature, finger prints, voice, iris,retina, hand geometry, ear geometry, and face.

Among these systems, facialrecognition appears to be one of the most universal, collectable, andaccessible systems. What is face recognitionFacial recognition (or face recognition) is abiometric method of identifying an individual by comparing live capture ordigital image data with the stored record for that person. Facial recognitionsystems are commonly used for security purposes but are increasingly being usedin a variety of other applications. The Kinect motion gaming system, forexample, uses facial recognition to differentiate among players. Some mobilepayment systems use facial recognition to securely trust users, and facialrecognition systems are currently being studied or deployed for airportsecurity. Face recognitionin general and the recognition of moving people in natural scenes, require a set of visual tasks to be performedrobustly.

Facial recognition systems based on faceprintscan quickly and accurately identify target individuals when the conditions arefavorable. However, if the subject’s face is partially obscured or in profilerather than facing forward, or if the light is insufficient, the software isless reliable. Nevertheless, the technology is evolving quickly and there areseveral emerging approaches, such as 3D modeling,that may overcome current problems with the systems. According to the NationalInstitute of Standards and Technology (NIST), the incidence of false positives infacial recognition systems has been halved every two years since 1993 and, asof the end of 2011, was just 0.003%Currently,a lot of facial recognition development is focused on smartphone applications.

Smartphone facialrecognition capacities include image tagging and other social networking integration purposes aswell as personalized marketing. A research team at Carnegie Mellon hasdeveloped a proof-of-concept iPhone app that can take a picture of anindividual and — within seconds — return the individual’s name, date of birthand social security number. There are manyadvantages associated with facial recognition. Compared to other biometrictechniques, facial recognition is of a non-contact nature. Face images can becaptured from a distance and can be analyzed without ever requiring anyinteraction with the user/person.

As a result, no user can successfully imitateanother person. Facial recognition can serve as an excellent security measurefor time tracking and attendance. Facial recognition is also cheap technologyas there is less processing involved, like in other biometric techniques.

 How Facial Recognition Systems Work As one of several methods of what are called “biometric”identification systems, facial recognition examines physical features of aperson’s body to uniquely distinguish one person from all the others. Otherforms of this type of work include the very common fingerprint matching, retinascanning, iris scanning (using a more readily observable part of the eye) andeven voice recognition.These systems take in data – often an image –from an unknown person, analyze the data in that input, and attempt to matchthem to existing entries in a database of known people’s faces or voices.Facial recognition does this in three steps: detection, faceprint creation, andverification or identification.

When an image is captured, computer softwareanalyzes it to identify where the faces are in, say, a crowd of people. In amall, for example, security cameras will feed into a computer with facialrecognition software to identify faces in the video feed.Once the system has identified any potentialfaces in an image, it looks more closely at each one. Sometimes the image needsto be reoriented or resized.

A face very close to the camera may seem tilted orstretched slightly; someone farther back from the camera may appear smaller oreven partially hidden from view.When the software has arrived at a proper sizeand orientation for the face, it looks even more closely, seeking to createwhat is called a “faceprint.” Much like a fingerprint record, a faceprint is aset of characteristics that, taken together, uniquely identify one person’s face.

Elements of a faceprint include the relative locations of facial features, likeeyes, eyebrows, and nose shape. A person who has small eyes, thick eyebrows anda long narrow nose will have a very different faceprint from someone with largeeyes, thin eyebrows, and a wide nose. Eyes are a key factor in accuracy. Largedark sunglasses are more likely to reduce the accuracy of the software thanfacial hair or regular prescription glasses.A faceprint can be compared with a single phototo verify the identity of a known person, say an employee seeking to enter asecure area. Faceprints can also be compared to databases of many images inhopes of identifying an unknown person. Exampleof facial recognition Face IDFace ID a formof biometric authentication. Rather than a password or a securitydongle or authentication app, biometrics aresomething you are.

Fingerprint recognition is also a biometric.Instead of oneor more fingerprints, as with Touch ID, Face ID relies on the uniquecharacteristics of your face. Apple is betting that its technology can meet sixseparate hurdles:·        Initially scan your face accurately enough torecognize it later.·        Compare a new scan with the stored one withenough flexibility to recognize you nearly all the time.

·        Scan your face in a wide variety of lightingconditions.·        Update your facial details as you age, changehairstyles, grow a mustache, change your eyebrows, get plastic surgery, and soforth to still recognize you.·        Let you wear hats, scarves, gloves, contactlenses, and sunglasses, and still be recognized. Face recognition advantages   The software can be used for security purposes in organizations and in secured zones.

The software stores the faces that are detected and automatically marks attendance. The system is convenient and secure for the users. It saves their time and efforts. Inexpensive technique of identification Face recognition disadvantages   The system doesn’t recognize properly in poor light so may give false results. It can only detect face from a limited distance.

Face recognition systems can’t tell the difference between identical twins.     Facing the FutureWhat the Future HoldsRobots with facial recognitiontechnology, overall, can help cut costs, be assigned tasks that are otherwisedifficult or impractical for humans or in areas with a clear deficit of humanresource. They will also play an important role in services that require a highlevel of accuracy.

Mobile robots like those by SMP Robotics can be used inrestricted areas for patrolling. If the system recognizes a human in the PTZ(Pan-Tilt-Zoom) camera image, it transmits an alarm signal to a guard station.After analyzing the video image, an operator can decide to reset an alarm, turnon a siren, or a turn on a strobe on the robot and send out security personnelto deal with the intrusion. In large facilities and factories, such robotsurveillance can add an extra layer of security.  Face Recognition and the Future of SecuritySensorstransforming businessBusinesses willtake advantage of face recognition to add another layer to their data security.As facial recognition re-enters the smartphone arena, you should expectcompanies to further adopt mobile technology in their business processes.Currently, mobile devices have become a vital business tool in the enterprise,especially in keeping tabs with offshore, mobile, and field-based workers.In fact, somebusinesses have initiated the use of smartphones and tablets in managingemployees’ hours of service and duty status to replace paper-based reports.

Forexample: The FederalMotor Carrier Safety Administration (FMCSA) announced the final ruling to bringin the Electronic Logging Device (ELD) that will affect drivers and fleetoperators across the United States. In a post about ELD compliance byFleetmatics, mobile gadgets will beused by drivers in logging their hours automatically while their managers willreceive real-time reports about their field employees, as well as being sentalerts to prevent violations. With the facial recognition sensor technology onmobile devices, this type of data will be kept safe and secure due to thisextra layer of security. CONCLUSION Face recognitionsystem presented in this term-paper contributes a resilient face recognitionmodel based on the mapping of behavioral characteristics with the physiologicalbio-metric characteristics. looking at the developments in facial recognitionover the recent years, we could be looking at people using facial recognitionto operate most thing in there day to day life such as TV and also they coulduse face recognition integrated with house hold security system.



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