Studying Real Time Application On College Student For Automatic Detection And Recognition Of Student

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).

Student ids can bring efficiency to the school in areas such as the library and cafeteria. Schools such as Owensboro High School use student ids to use as public library cards, to buy lunches, to get into athletic events, and even to check out books from the school library(Ramsey). If it was possible to scan student ids, the lunch lines in the cafeteria would decrease in size. Also, it will ease the process to get a public

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.

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.

Marin Kaste wrote the article “A Look Into Facebook’s Potential To Recognize Anybody’s Face.” This article discusses the challenge of using facial recognition software to determine an individual’s name. The software used for facial recognition has numerous defects, which causes problems when trying to identify an individual using a poor quality photo. Another problem with facial recognition software is if an individual is not in the database, then they cannot be found using the software. The article explains that the problems of facial recognition could be solved by collecting all of the photos of individuals on Facebook to create a universal database.

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.

Face recognition has attracted great attention in recent years. An important application of face recognition is to assist law enforcement. For example, Uhl and lobo [1] proposed the first automatic retrieval of photos using a query sketch based on face recognition algorithm and more recently Klare and jain [2] suggests an effective method of matching sketch photo using many technique such as local descriptors similarities algorithm .Once this forensic sketch is ready, it is disseminated to law enforcement officers and media outlets hoping that someone might be knowing the suspect. The first approaches developed by Tang and Wang (2002, 2003, 2004) [3] use global linear transformations, based on eigenface method to convert

Recognition Rate (RR): This is the amount of the possibility that the system recognizes a face correctly that is among the trained faces or rejects a face not among the trained faces, that is summation of the true positive and true rejection divided by the total number of test attempts. In this work we term the True Positive (TP) as the the correct number of people the system is able to truly identify when the real probe set (44 images) is used and True Rejection is the number of people the system rejected as not identified when any of the unknown images are used. Mathematically, it is calculated as (Chukwuradibia, 2015).

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.

An authentication method based on face recognition is designed for restricting access of incoming call for un-authorized entity. It will take the image of person (who wants to be registered as an authorized entity) during the registration process, once the registration is complete, it will monitor the entity while call receiving. Therefore the user can not receive the call unless the application will grant him as an authorized entity. For this purpose application has to monitor the call status and as the call status goes to incoming call, application has to restrict the receiving of call and take a photo of claimed entity by the same camera of mobile on which the call is coming. Once the image is captured, it will go through the

Abstract: -Face recognition system presents a challenging problem in the field of image processing and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Many researches in face recognition have been dealing with the challenge of the great variability in head pose, lighting intensity and direction, facial expression, and aging. One of them is Identical twin face recognition is a challenging task due to the existence of a high degree of correlation in overall facial appearance. The purpose Identical twin face recognition is mainly focus in the area of security. In this paper we can compare the techniques to identify the twins and techniques are facial aspects and facial marks.

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.

Face recognition has been a topic of active research since the 80’s, proposing solutions to several practical problems. It has been a challenging job for the researchers to develop a facial recognition system with 100% accuracy because of all the difficulties and limitations. As we know that the human face changes after a short period of time so no facial recognition system can work perfectly after a few years. It has to be updated with the latest database images of the person in order to verify the person. Also wearing spectacles, mask, mustaches may also affect the output of the face recognition system. Face recognition is a biometric which is much easier to understand, because we recognize or identify different people mostly by their faces. However the recognition process used by the human brain for identifying faces has not a concrete explanation. It has now become essential to have reliable security systems in