Linear Discriminant Analysis

Most police departments still rely on officers to verify that the suspect chosen by the face recognition software actually matches the camera footage. However, humans shockingly make an error in this process once in every two cases (Bedoya, Alvaro, et al 2016). In some instances, it is not only this human error that is leading to false convictions but rather the system itself. A study, co-authored by the FBI, noted that the facial recognition software is less accurate when identifying African Americans. Systems relying on mugshot databases have a disproportionate number of African Americans due to their high arrest rates in America. This creates “racial biased error rates” that perpetuate implicit and systemic racism in our society (Bedoya, Alvaro, et al 2016). This presents yet another reason regulations should be put in place solely to limit the use of this technology to cases where its use is essential to solving a crime.

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.

Facial recognition is a technological product of the digital age that is continuing to evolve. The efficiency of the technology is an asset to crime detectives apprehending criminals, or the government tracking suspected terrorists for the safety of the country. It can also be used on a corporate level to allow a business to understand their ideal customer, or to increase the intractability of their website. While these abilities are positives to the people using them, the data collection may be harming more than it is helping. Considering the benefits of facial recognition, it is important for people to see what they are giving up for a more efficient experience. Facial recognition technology forces users to relinquish control of their own

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).

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.

In effect, people are unknowingly being put in suspect lineups without their awareness or consent. This can lead to false accusations against innocent citizens. Most police departments still rely on officers to verify that the suspect chosen by the face recognition software actually matches the camera footage. However, humans shockingly make an error in this process once in every two cases (Bedoya, Alvaro, et al 2016). In some instances, it is not only this human error that is leading to their conviction but rather the system itself. A study, co-authored by the FBI, said that the facial recognition software is actually less accurate when it comes to identifying African Americans. Systems relying on mugshot databases have a disproportionate number of African Americans due to their high arrest rates in America. This creates “racial biased error rates,” that perpetuate implicit and systemic racism in our society (Bedoya, Alvaro, et al 2016). But for American citizens in general, in any crime being solved by using face databases, anyone is a potential suspect. Because of this, regulations should be put in place to limit the use of this technology to cases where its use is relevant and vital to solving the issue.

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.

For many generations the idea of a device that could recognize you simply by your eyes has been the stuff of science fiction. It was an invention that seemed intangible. However, over recent years this imaginative and seemingly futuristic technology has become a thing of the present. Each iris has a unique pattern, like fingerprints, however iris scans have proven to be more accurate and distinct. Slowly but surely, this novel technology is making its way into the everyday lives of Americans. For example, colleges, such as George Mason University have begun to use iris scans as a form of identification in cafeterias; even airports have started to introduce this innovation (MacRumors, 2014). Not only this, but the invention has been

A filter was applied to all faces, especially stronger to the African-American’s and Indian’s faces to lighten the skin tone, hence they do not stand out too much (refer to Figure 1 in Appendix). The order of photos shown to participants are randomized using excel and were shown one by one instead of going by pairs, subtle differences would best be testified by implicit preference instead of obvious comparison. Photos are sorted at the time when participants arrive o the first round of data collection, and the rating sheet was created on a separate sheet. It was modified in the second round of data collection with sorted randomized order of photos with corresponding rating scale beneath the pictures before hand for better efficiency and accuracy (refer to Figure 2 in Appendix). A follow-up question was attached after rating the photos – “do you recognize this face” to avoid personal preference or bias towards to pictures beforehand, which could possible skew the rating instead of what we would like to test. During the second round of data collection, the rating and photos are presented one by one in a single sides piece of paper, followed up by a modified close-ended question – “do you already know who this person is before this experiment” to confirm whether the participants recognize the person or seen the

We live in a world today, in which technology moves at a very rapid pace. Many of these technological advances can be used to make our everyday lives easier and safer. One of these new technologies is Biometrics. Biometrics is the process of measuring a person’s physical properties. This would include measuring things like fingerprints, retinas, odor, vein structure on the back of the hand and many other things. Biometrics is a very important topic because it would create better security precautions for certain places that need to be secure. Biometrics will make our society safer by only allowing authorized people out of secure facilities and by keeping the unauthorized people out. Throughout the rest of this

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).

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,