Techniques Used For The Real Time Applications Is On The Face Recognition Through Different Illumination

According to this hypothesis, face-specific mechanisms can be activated when it is necessary to make detailed discriminations between exemplars within a specific category (Gauthier et al., 1999a, 2000b). Furthermore, when a face is recognized as a face, the identity of the face is also identified where as when non-face objects are identified it is common only to identify them with a general category such as car or bird. Therefore, according to this model face recognition calls on domain-general methods for identifying specific exemplars within a category – this is also done when non-face objects are identified (Gauthier et al., 1999a,

Biometrics technology aims at utilizing major and distinctive characteristics such as behavioral or biological, for the sake of positively indentifying people. With the help of a combination of hardware and specific identifying sets of rules, a basic human attribute, automated biometric recognition mimics to distinguish and categorize other people as individual and unique. But the challenges surrounding biometrics are great as well.

The digital image of the face of a person can be matched against a record of other images by using face recognition software. In case that some of the images in the database go with the digitized image, the owner is reported about it by the system. Automatic face recognition has been studied and investigated extensively since 1990s and its usage is turning out to be no-nonsense in the present times. Although a number of automatic face recognition applications are relatively agreeable and harmless (access regulation to armaments, currency, illegal proof, nuclear equipment/supplies etc), there are still several dangers of face recognition systems that include violation of privacy and civil liberties, unrestrained exploitation, identity theft, illegal use of database, free access to personal data on social media etc. (Agre, 2001).

Facial recognition is a “one to many” process of searching a large database for individuals having similar features as the probe (Suspect). Facial Recognition is used as a “lead generator only” and should be considered as a tip only, it does not provide a positive identification of an individual. This is similar to inputting a latent print into the Automated Fingerprint Identification System (AFIS) and having ten candidates returned, they are only similar in nature.

Face recognition is another biometric technology. Face recognition uses the same technology that iris recognition uses. For face recognition, a camera takes several images of a person to find out who it is. Face recognition differs from all of the other biometric technologies because the person that is in the picture does not have to cooperate with the process. In all of the other technologies it requires the people to actively participate in the process. In face recognition, the image can be taken without the person even knowing that it took place.

Through this routine of advanced technology analysis, it has been established to increase the results and have hastened the procedure of identifying suspects of crimes. Facial recognition is also necessary for public involvement and observation as it also aids law enforcement officials to more easily zone in on possible suspects of a crimes being caught. With the use of facial recognition, it constantly has been proven quite an effective method with the incorporation of this technique.

After reading the digital image into internal memory, the program uses cvThreshold function to transfer the colorful image into a grayscale one. Then according to the optimal variance, transfer the grayscale image to a binary image. After that, the program uses cvDilate and cvErode functions to do dilation and erosion operation. Thus, in order to improve the accuracy rate, cvSmooth function is used to smooth the edges of the image. Then program uses canny operator to detect and outline edges. At the end, circle hough transform is used to detect the circles in the images, which are the sign of human head. So the program

Biometric recognition plays an important role in the field of security for any system. For embedded system it plays a significant role. As we know ATMs and smart phones are the most used smart devices that we interact daily, is needs to be secured. For this reason it must have a secure system that can provide security to save our personal things. For securing them there are lots of ways that are introduced in the past years. Biometric recognition is one of them. In the field of biometric recognition face, fingerprint, voice and retina are used to recognize an individual. Iris recognition is one of them. (Jain, A.K, 2004) Every human has a different body characteristic. One will never be same like another. Eye is one of them.

We have made a scanner in which it scans the face and looks your facial features. Depending on how many features match with the picture obtained you will be granted access to the area you wish to go to. Facial Recognition is a kind of security measure that will be used in the future in order to grant access into places or computer programs. Facial Recognition is and will not only be used to access places or computer but it is also currently being used to gather demographic data on crowds. In some cases facial recognition is already being used to open banking accounts.

1970: Goldstein, Harmon, and Lesk used 21 specific subjective markers such as hair color and lip thickness to automate the recognition.(2) However, due to the lack of sophisticated computer, the measurements and locations were miscalculated.

The process of making an identification based off the method of facial recognition is far more advanced. Facial recognition measures distinguishing facial features such as the dimensions of the nose, the distance between eye sockets, the slope of the forehead, the line and size of the jaw, and the contours of the cheeks (Dewey et al., 2013). Once the subjects photograph is obtained by the specific system, it uses the above parameters to compare the subjects photograph to one which had been previously taken and stored in the organizations

Finally, face recognition starts at infancy and is utilized throughout one’s life. A person must utilize their long term memory for face recognition. A person must give their full

Bruce and Young’s theory of recognition tells us that human’s extract several kinds of information from faces; and that there are eight different components of such information. Such as structural encoding, expression analysis, facial speech analysis, directed visual processing, face recognition nodes,

Automatic face recognition has always been a major focus of research for a few decades, because of numerous practical applications where human identification is needed. Compared to other methods of identification (such as fingerprints, voice, footprint, or retina), face recognition has the advantage of its non-invasive and user friendly nature. Face images can be captured from a distance without interacting with the person, which is particularly beneficial for security and surveillance purposes. Furthermore, extra personal information, like gender, face expressions or age, can be obtained by further analyzing recognition results. Nowadays, face recognition technology has been widely applied to public security, person verification, Internet

Biometric technologies are getting better and finely tuned. The rate of false readings and errors has sharply fallen. However it still requires careful consideration and planning to implement a biometric identification system. They are most costly and complicated to implement as compared with other authentication systems. A proper evaluation of the system is important before purchasing any biometric system. A thorough risk analysis is necessary. In many cases biometrics may be overkill. Biometrics must be used if there is high level of risk involved. Customer acceptance is also important when logging on to company websites. Home users might not be ready to install biometrics on home computers for online banking.