CHAPTER 1 FACIAL RECOGNITION SYSTEM
1.1 INTRODUCTION
A biometrics is, “Automated methods of recognizing an individual based on their unique physical or behavioral characteristics.” For example face, fingerprint, signature, voice etc. Face recognition is a task humans perform remarkably easily and successfully.
In face recognition Features extracted from a face are processed and compared with similarly processed faces present in the database. If a face is recognized it is known or the system may show a similar face existing in database else it is unknown.
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
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).
Secondly, face recognition units contain stored descriptions of known faces. When a familiar face is seen, face recognition units send signals to cognitive system and active person identity nodes. Person identity nodes allow access to semantic information about the person. The impairment
I concur with you on the use of biometrics by the government, and especially facial recognition to apprehend criminals. The recent rise in criminal cases can be halted if such a system is deployed. Biometrics can never go wrong and is in fact one of the most accurate ways of identifying people. If the government can be able to launch a system that can capture personal specifications, it can be really helpful.
Developed in the 1960s, facial recognition technology has been used by the government and companies to identify people by matching them to photos. The data for this software was originally entered manually, limiting the scope of use. By 2001, the novelty of more powerful facial recognition technology grasped the public’s attention. During the January 2001 Super Bowl, surveillance cameras captured images to find people with a criminal record (FBI 2013). This potential invasion of privacy under the pretense of public safety sparked a public debate about what private information the government was allowed to take from us. So should we be putting limitations on the use of facial recognition software in America in order to keep
Biometrics is a method of identifying an individual based on characteristics that they possess, typically physiological features such as a fingerprint, hand, iris, retina, face, voice, and even DNA. Some methods of biometrics security even use multiple physiological features or multimodal biometrics to provide superior security than a single form of biometrics can provide. Why are biometrics important in the field of information security? Biometrics provide a remarkable amount of security for information because biometrics are unique to each person, and thus cannot be lost, copied, or shared with another individual. This security allows for biometrics to provide a means to reliability authenticate personnel. The importance of biometrics can be further divided into the history of biometrics and why it was devised, past implementations of biometrics, current implementations of biometrics, and future implementations of biometrics.
To what extent should governments and companies be using biometric information obtained from facial recognition technology for surveillance and convenience in identifying individuals in society? This article discusses the legislature that must be implemented to protect our right to privacy. We will reach a conclusion by further analyzing the benefits and the risks of the new technology, evaluating the privacy issues that accompany, and discussing faults in the
The face recognition model developed by Bruce and Young has eight key parts and it suggests how we process familiar and unfamiliar faces, including facial expressions. The diagram below shows how these parts are interconnected. Structural encoding is where facial features and expressions are encoded. This information is translated at the same time, down two different pathways, to various units. One being expression analysis, where the emotional state of the person is shown by facial features. By using facial speech analysis we can process auditory information. This was shown by McGurk (1976) who created two video clips, one with lip movements indicating 'Ba' and other indicating 'Fa'. Both clips had the sound 'Ba' played over the clip.
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.
This essay will talk about face recognition and several reasons why it has been studied separately. The ability to recognise faces is of huge significance of people’s daily life and differs in important ways from other forms of object recognition (Bruce and Young, 1986). Than this essay will talk about the processes involved in face recognition which comes from the diversity of research about familiar and unfamiliar faces-it includes behavioural studies, studies on brain-damaged patients, and neuroimaging studies. Finally, it will discuss how face recognition differs from the recognition of other object by involving more holistic or configuration processing and different areas of the brain (Eysenck & Keane, 2005).
This report is intended to develop an understanding of Basic Biometrics and how facial recognition is used by law enforcement to assist in the solving of crimes. Especially when there is little or no physical evidence to be pursued. Most individuals only see advanced levels of technology in television shows or the movies and believe, that must be how the systems work, this is commonly referred to as the “CSI Effect”. This effect can have a profound effect on juries, City councils or civic groups as they try to interpret what is being discussed while viewing events through a kaleidoscopic lens created for sensationalism on television.
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
The Report presents a hybrid neural network solution, which compares favorably with other methods and recognizes a person within a large database of faces. These neural systems typically return a list of most likely people in the database. Often only one image is available per person. First a database is created, which contains images of various persons. In the next stage, the available images are trained and stored in the database. Finally it classifies the authorized person’s face, which is used in security monitoring system. Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. Face has certain distinguishable landmarks that are the peaks and valleys that sum up the different facial features. There are about 80 peaks and valleys on a human face. The following are a few of the peaks and valleys that are measured by the software: