Essay Example on Facial Recognition: Verifying Identity with Biometric Data

Introduction

Facial recognition is the method of recognizing or confirming a person's identity using their face. The process of facial capture converts analog (a face) data into a collection of digital data based on the facial characteristics of the person. The method of the face match verifies that two faces belong to the same individual. Facial recognition technology gathers data from an image or video, using biometric data to trace facial features. It relates the data with a database faces to detect a match. Facial recognition technology uses a camera database to identify individuals in security images and videos (Wright, 2018, pg. 611). This utilizes biometric data to track the facial characteristics and help verify identification across main facial features. It lists more than 60 facial features; it tests and then calculates a number to illustrate the proportional distances combined.

Is your time best spent reading someone else’s essay? Get a 100% original essay FROM A CERTIFIED WRITER!

Save 25%

Automated facial recognition pioneers include Bledsoe, Helen Wolf, and Bisson. Bisson experimented between 1964 and 1965 on using the computer to identify human faces. Face camera recognition software systems developed with maturing AI, are capable of recognizing and interpreting intricate patterns in forms similar to human brains (Petrescu, 2019, pg. 238). The basic structure is the basis when contrasting between faces, such as the range from the front to the chin and the range between the eyes. As this changes relative distances, the angle of the face as it applies to the facial recognition system must be calculated as well.

Essential Steps on How to Face Recognition Technology Works

Fundamentally, the face-recognition process takes place in two stages. The first includes the collection and selection of features, and the second is object detection. The first step is to take a photograph of one's face that is taken from a photo or video. The second stage comprises recognizing the geometry of one's face. The main variables include the range from one's eyes to the distance between the head and the chin (Sati, 2018, pg. 235). The program recognizes facial landmarks, which are essential to identifying one's face and contributes to the signature of one's face. A mathematical formula, one's facial signature, is related to a database of recognized faces. Determination is then achieved by matching the image in the database of facial recognition technology.

Uses of Facial Recognition Technology

Facial recognition technologies are used by various companies and individuals in many different locations worldwide. For instance, the U.S. government utilizes facial recognition systems at airports since these systems can track people arriving and departing from the airports (Sati, 2018, pg. 232). The Homeland Security Department has made use of the system to recognize individuals who have overstayed in the United States or those who may be under criminal examination. Law enforcement may also be using smartphones during military operations to identify suspects. Smartphone manufacturers use facial recognition technology in their various devices. For instance, Apple utilized facial recognition to open the iPhone X for the first time and has continued using it with its subsequent iPhone models (Petrescu, 2019, pg. 240). Also, many telecommunications manufacturing firms have used this technology to develop the safety features of their devices for their customers around the world.

Facial recognition technology is also used for taking roll calls in the classes at colleges and universities. It is also used on websites in social media companies to protect their customers' privacy. For example, when one uploads a picture to its website, Facebook uses an algorithm to recognize faces (Wright, 2018, pg. 611). Also, it is often used at entrances and secured areas in many companies across the world. Some businesses have exchanged security badges for facial recognition devices. Face recognition has also been used in smarter advertisements, as it has the potential to make ads more personalized by making informed assumptions about the age and gender of individuals. Organizations like Tesco now intend to install displays with built-in facial recognition at petrol stations (Petrescu, 2019, pg. 252). With time, face-recognition will be used in advertisements. Face recognition has been used to find the missing children and victims of domestic violence and human trafficking.

Listerine has created a pioneering facial recognition software that uses face recognition to support the blind. The app detects when persons smile and inform the vibrating blind user, which helps them to understand social situations better. Portable face recognition devices, for example, one provided by FaceFirst, are now supporting law enforcement officers by assisting them to recognize persons from a safe distance in the field instantly (Sati, 2018, pg. 234). This can help them by providing them with qualitative data informing them about who they are engaging with and how to proceed cautiously. Facial recognition can assist forensic operations by identifying persons automatically in surveillance images or other recordings. Face recognition tools may also be used to recognize people who are dead or unconscious at murder scenes.

Face recognition systems have been used to diagnose illnesses that cause noticeable changes. Face recognition will become an essential screening method for all types of conditions as algorithms become ever more advanced. Face recognition security systems can be immediately detected when excluded students, hazardous parents, drug dealers, or other persons enter school premises, which poses a danger to school security (Wright, 2018, pg. 611). Face recognition will lower the risk of acts of violence by informing the security personnel in real-time. The technology can be used to ensure people using ATM cards are who they claim they are.

Conclusion

Conclusively, the technology of facial recognition has been of benefit to people all over the world. It has the potential to classify persons by number, as it does not allow the test subject to function to comply. Properly built systems placed in airports, cinemas, and other public spaces will distinguish people within the crowd, without even people recognizing them. An algorithm decides the best match, and the percentage of likelihood of accuracy is given as compared to a database of stored mathematical models of known faces. The enhanced skill of the system is seen in additional accessible related details, such as skin tone, clothing color and style, backpack identification, vehicle type, and traveling direction. These features enhance security, which has been the main threat to people in the 21st Century.

References

Petrescu, R.V., 2019. Face Recognition as a Biometric Application. Journal of Mechatronics and Robotics, 3, pp.237-257.

Sati, V., Garg, D., Choudhury, T. and Aggarwal, A., 2018, November. Facial Recognition-Application and Future: A Review. In 2018 International Conference on System Modeling & Advancement in Research Trends (SMART) (pp. 231-235). IEEE.

Wright, E., 2018. The future of facial recognition is not fully known: Developing privacy and security regulatory mechanisms for facial recognition in the retail sector. Fordham Intell. Prop. Media & Ent. LJ, 29, p.611.