Comprehensive Report: Facial Recognition Software Issues and Solutions

This report provides a comprehensive overview of facial recognition software, beginning with an introduction to the technology and its applications. It defines the core issues associated with facial recognition, such as potential inaccuracies due to changes in facial features over time or inconsistencies in databases, and the significant privacy concerns related to the storage and use of biometric data. The report presents research findings on the technology's applications in various domains, including ATM systems, healthcare, and surveillance, while also highlighting the challenges of face recognition, especially with large databases and variations in facial expressions and aging. The report proposes solutions to address these issues, such as designing software that accounts for aging and enhancing the security of databases to prevent unauthorized access to sensitive data. In conclusion, the report summarizes the key aspects of facial recognition technology, the challenges it faces, and the proposed solutions to ensure its effective and ethical implementation.

Running head: FACIAL RECOGNITION SOFTWARE
FACIAL RECOGNITION SOFTWARE
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Table of Contents
1.0 Introduction........................................................................................................................2
2.0 Definition of the issue.......................................................................................................2
3.0 Research findings.............................................................................................................4
4.0 Proposed solution.............................................................................................................4
5.0 Conclusion.........................................................................................................................5
6.0 References.........................................................................................................................6

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1.0 Introduction
A facial Recognition system specifically refers to the technology that carries
the capability of identifying or as well verifying a specific individual from an existing
digitalized image or a video frame from a specific source of video. There is an
existence of a number of methods particularly in which, the system for facial
recognition works. However, in general the system works by comparing the existing
features belonging to the face from a provided set of images present within the
related database (Klare et al., 2015). This technology also puts forward the Biometric
Artificial Intelligence1 that is completely based upon the application of uniquely
identifying a person by the analysis of the related patterns present upon the face of
the individual to be specific.
However, there are certain issues related the technology of the facial
recognition. Such as, if the person’s face gets disrupted due to the occurrence of
certain accidents, then the software system having the former face will not at all
identify the individual’s face until and unless the system gets hold of the same face
to be approx. (Amos, Ludwiczuk & Satyanarayanan, 2016). This research has been
carried out to specifically aim at the issues along with that of the limitations that exist
within the technology of facial recognition2.
2.0 Definition of the issue
Facial Recognition is commonly referred to the method of recognizing the face
of a human with the help of technology to be specific. The system of facial
recognition makes use of biometrics to map all the features present upon the face
specifically extracted out from a photo or maybe a video. The system particularly
compares the information present within the database containing all the information
belonging to the faces to be matched whenever an individual tries to access the
system with the help of the its face to be specific (Sharif te al., 2016). The technology
belonging to that of the facial recognition can provide with a helping hand towards
1 This is used for the significantly maintaining the several authentication mechanisms that will be accurately
measured with the help of artificial intelligence technology.
2 There are several researchers associated within this field that suggests the importance of the biometric
authentication related with the artificial intelligence thus providing enhanced security within the specified
devices.

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the verification of an individual’s personal identity, but also has the inclusion of a
number of issues belonging to that of privacy3.
The technology of facial recognition works in a series of steps that has been
approached below in greater detail (Chen, Huang & Lv, 2017). The steps that are
generally carried out within the procedure of facial recognition are,
 A picture of the face that needs to be identified is captured from any of the
existing source to be specific.
 The software belonging to the facial recognition technology specifically reads
the geometry of the face belonging to the individual.
 Following this, the facial signature of the individual is created with the
utilization of a mathematical formula that is specifically stored within the
database to be compared at the time of recognition.
 The final step includes the determination of the face along with the picture
present within the database that necessarily belongs the respective individual
taken into consideration.
The technology of facial recognition is considered very much less effective if the
related facial expressions vary from the original data is stored specifically within the
database4. A broad smile across the face of the individual can lead the system to be
less effective towards the recognition of the system.
There also exist the inconsistency within the database that is specifically
being utilized by the researchers. On the other hand, the privacy of data is
considered to be the main concern when it comes down to the methods of storing
the biometrics related data within the business organizations. Data stores completely
belonging to the storage of the biometrics and the related data can be accessed by
the third party existence if the related data has not been stored properly or has been
hacked (Hossain & Muhammad, 2015). These are the major issues or the concerns
related directly to the technology belonging to the methods of facial recognition.
3 This technology is basically used in the digital devices such as mobile, laptops as well as these are used by
many effective application which stores user data thus providing enhanced security to them.
4 Database is significantly used in respect to the storage of the facial data, however cloud technology is used for
storing the overall facial data for future authentication purposes.

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3.0 Research findings
Facial recognition technology has always been considered as one of the
interesting area as well as one of the most challenging tasks in the related fields of
computer vision as well as the procedures belonging to image retrieval. This
particular technology has it availability to a number of domains such as the likes of
ATM, the systems related to healthcare, the driving licenser system, reservation
system belonging to that of the railway, the operations belonging to the surveillance
as well as the authentication of the passports (Singh & Prasad, 2018)5. In reference
to the larger database, the facial image recognition has always been undertaken as
one of the most challenging tasks while performing.
Face in the current form having the inclusion of a number of features entail
such related characteristics that may change over a period of time, such as that of
aging, which consists of a prompt importance within the related field of face
recognition. The variant of age is important also for the visual observation as well as
the retrieval of image after a long gap6 (Martinez & Valstar, 2016). The technology of
facial recognition depends entirely upon the features such as the likes of extraction,
particularly concerned about the data extraction along with the inclusion of some
basic features properties such as wrinkle, spot eyebrow, marks, makeup and the
other existing features.
Iris is considered to be one of the most important aspect present upon the
face, as well as the extracted feature having played a vital role within the analysis of
the biometric related to the face (Ding & Tao, 2016).
4.0 Proposed solution
In reference to all the issues that have been arising as concerns in regard to
the proper working of the software belonging to the facial recognition technology.
The issues related to the aging of an individual shall be considered as one of the
primary steps towards the upgradation of the software related to the technology of
facial recognition (Al-Kawaz et al., 2018). The software needs to be designed in such
5 The significant usage of this authentication procedure is associated with the banking transaction systems or
systems related financially.
6 Age puts a significant effect but the biometric system which uses the retina of the eyes remains fresh till the
device exists.

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a way that the aging of the respective individual does in no way affects the
procedure of recognition7.
In addition to this, the databases belonging to organizations within the field of
business need to have a proper security upon the data that specifically belongs to
the customers or the employees of the respective organizations (Hsu & Chen, 2015).
Security of the data existing within the database of the facial recognition needs to be
properly protected so that the third party individuals or the organizations do not have
the unauthorized access to the information specified8.
5.0 Conclusion
The above report can be concluded taking into consideration a number of
points, which specifically relates to the idea of Facial Recognition technology along
with the issues that have been considered as the rising concerns alongside. The
report puts forward the entire idea of what facial recognition is along with the brief
discussion of how the technology of facial recognition necessarily works. In addition
to this, the report identifies the number of concerns that has been rising with the
usage of the software working within the field of facial recognition. A number of
research findings have also been included down the report, and the proposed
solutions have been put forward as a conclusion to the discussion of the report.
7 Management Information System are depicted to be the collection of the hardware as well as the software
mechanisms which significantly allows the organization to provide timely information required for making teh
effective decisions.
8 The security of the overall data is a necessary approach that is related with the biometric authentication
procedure associated with the digital devices.

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6.0 References
Al-Kawaz, H., Clark, N., Furnell, S. M., Li, F., & Alburan, A. (2018, June). Advanced
facial recognition for digital forensics. In 17th European Conference on Cyber
Warfare and Security(pp. 11-19). Academic Conferences and Publishing
International Limited.
Amos, B., Ludwiczuk, B., & Satyanarayanan, M. (2016). Openface: A general-
purpose face recognition library with mobile applications. CMU School of
Computer Science, 6.
Chen, Z., Huang, W., & Lv, Z. (2017). Towards a face recognition method based on
uncorrelated discriminant sparse preserving projection. Multimedia Tools and
Applications, 76(17), 17669-17683.
Ding, C., & Tao, D. (2016). A comprehensive survey on pose-invariant face
recognition. ACM Transactions on intelligent systems and technology
(TIST), 7(3), 37.
Hossain, M. S., & Muhammad, G. (2015). Cloud-assisted speech and face
recognition framework for health monitoring. Mobile Networks and
Applications, 20(3), 391-399.
Hsu, H. J., & Chen, K. T. (2015, May). Face recognition on drones: Issues and
limitations. In Proceedings of the First Workshop on Micro Aerial Vehicle
Networks, Systems, and Applications for Civilian Use (pp. 39-44). ACM.
Klare, B. F., Klein, B., Taborsky, E., Blanton, A., Cheney, J., Allen, K., ... & Jain, A.
K. (2015). Pushing the frontiers of unconstrained face detection and
recognition: Iarpa janus benchmark a. In Proceedings of the IEEE conference
on computer vision and pattern recognition (pp. 1931-1939).
Martinez, B., & Valstar, M. F. (2016). Advances, challenges, and opportunities in
automatic facial expression recognition. In Advances in face detection and
facial image analysis (pp. 63-100). Springer, Cham.
Sharif, M., Bhagavatula, S., Bauer, L., & Reiter, M. K. (2016, October). Accessorize
to a crime: Real and stealthy attacks on state-of-the-art face recognition.

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In Proceedings of the 2016 ACM SIGSAC Conference on Computer and
Communications Security (pp. 1528-1540). ACM.
Singh, S., & Prasad, S. (2018). Techniques and Challenges of Face Recognition: A
Critical Review. Procedia Computer Science, 143, 536-543. doi:
10.1016/j.procs.2018.10.427