AI Based Face Detection Software: Implementation, Design & Analysis

This report discusses the implementation of face detection software driven by artificial intelligence for enhanced security systems. The primary goal is to identify individuals accurately and grant them access. The report covers various aspects, including the problem domain, purpose, justification, and conceptual framework. It details the methodology, including face detection modules, internal software design, database description using MATLAB, and data collection methods. Ethical considerations, such as potential misuse and technical faults, are addressed, along with compliance requirements. The report also presents a project plan with deliverables and recommendations for improving system security and affordability. It concludes that while the implementation is complex, it offers significant benefits with proper project management and ethical considerations.

Running head: FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
Name of the Student:
Name of the University:
Author Note:

1FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
Introduction
The face detection software is a system which is driven by the artificial intelligence. The
main purpose of this face detection system is to identify the right persons and give them the
access. This system can be used in the smart security system (Zafeiriou,Zhang & Zhang,2015).
The main objective of this paper is to discuss about the implementation of the face detection
software. In order to do these different aspects of the usage of face detection software along with
the planning of the development phase has been given in this paper.
Problem domain:
The paper is mainly focused on the implementation and significance of the face detection
system. The face detection system is driven by artificial intelligence, where the system can
retrieve data after scanning the face.
Purpose and justification:
The purpose of this implementation is to develop a system that will scan and detect the
face and will retrieve the data regarding that face (Bhatia, Lilhore & Agrawal, 2017). This
system is drive by the artificial intelligence where the software or the machine will able to
identify different faces.
The implementation of this software is justified as it can be helpful in the development of
the advanced security system at organizations. Moreover using this kind of software the
implementation of the security system at smart home projects can be achieved.
Recommendations of the supervisor:

2FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
The recommendation of the supervisor is focused on the right implementation of this face
detection software. It can be recommended that the security system of the software itself is
needed to be well maintained (Galbally, Marcel & Fierrez, 2014). The usage of the software is
needed to be simple so that the users can operate the functions of the system easily.
Conceptual framework:
The concept of face detection system develops a unique way of providing security and
authentication.
At the initial state, the faces of different persons along with the requires details are
scanned into the system. Before entering into the premise of the housing or the organization the
software will scan the face of the person (Lee et al.,2018). In case, if the face is matched with the
images from the database, the system will let that person to enter the premise, else it will
recognize that person as intruder. Different image filters along with the smart sensor techniques
are also used in the implementation of the system.
Methodology
Research and system development methods:
The development of this system contains different modules.
Face detection:
The primary function of this module is to detect the face filtering algorithm. This
algorithm extracts and identifies the pattern of the face and eyes.
Internal design of the software:

3FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
The internal design of the software allows the face detection system to be synchronized
with the other controls (Wang, 2014) . The connection with the image bank stored in the face
detection system with the database regarding the information is established through this
software.
Description of database:
Maintaining the database regarding the face detection can be implemented through the
use of MATLAB software.
Data collection method:
The methodology used in this paper is derives from already published journals and
research articles. In this case, it can be said the data used in this development is secondary data
(Irgens et al.,2017). Apart from that the comparison of this system with the other system requires
data from the evaluation of the other system. The data is mainly quantitative data that shows the
performance of different system.
Ethical issues:
The use of face detection and reorganization system has lots of advantages over the
conventional data system (Simpson et al.,2017). However, it has some ethical issues (Böhm et
al.,2017). The face detection system can be misused by the intruders. Apart from that the lack of
security in the system can cause security threat. Another ethical issue can be raised from the
technical fault. In some cases due to the technical fault, the system may not permit the authorized
person to enter into the system , while it can permit the access to the wrong person in the system.
Compliance requirements:

4FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
In order to implement the system at any institution or housing complex certain
equipments are needed. In order to implement this technology, a system dedicated to perform the
task is needed (Sparavigna,2016). This system can be expensive as the face detection system is
not a conventional way of providing security. Apart from that the security using face detection
system can help maintain laws and regulations as it can clearly identify the intruders (Jridi &
Alfalou, 2017). However, there are no certain policies and regulations of using this system.
Analysis of data:
The analysis of data is done on the basis of data collected from the articles and journals.
The data shows the effectiveness of using face detection system as the security equipment
compared to the conventional system.
Project Plan and duration

5FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
WBS

6FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
Development of face
detection software
Initialization of the
project
Requirement
gathering and
documentation
Planning
Design of the face
detection software
desiging of the
interface
Software coding
Creation of database
interface
generation of
connection between
face dtection
software and
database
testing of the
software
Monitoring the
performance of the
software
closing of the
project regarding
the development.
Deliverables
The deliverables for development of the system is following-
 The documentation of the system where the design and the requirements are mentioned
clearly.
 The system with the proper functioning modules.
Software which is used in the course of development is clearly mentioned in the
documentation and planning. On the other hand a separate document with the code of the
software is provided with the documentation of the system.

7FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
Recommendations:
Certain recommendations are made on the basis of the functioning of the system.
 The security of the system can be improved using different security protocols.
 Certain rules and regulations can be implemented for the face scanning feature of this
system.
 The price of the system can be lowered so that the system can be affordable.
Conclusion
It can be concluded from the above discussion that the implementation of the face
detection software using artificial intelligence would be beneficial. However, the development
and the implementation method of this software is complicated. Proper project management plan
is needed to be implemented in order to carry out the implementation in a proper way. Certain
recommendat9ions are made on the basis of ethical issues related with the usage of this system.

8FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
References
Bhatia, K., Lilhore, U. K., & Agrawal, N. (2017). An Efficient Face Detection and Recognition
Method Based on Semi-Supervised Learning with Improved LPP Projection Method.
Böhm, T., Engel, F., Bzdok, D., Schneider, F., & Hemmje, M. (2017, November). Approach to
semi-automatic labeling of video sequences for affective computing-enabling the
comprehensive assessment of emotion detection software from mimics. In Bioinformatics
and Biomedicine (BIBM), 2017 IEEE International Conference on (pp. 1996-2000).
IEEE.
Galbally, J., Marcel, S., & Fierrez, J. (2014). Image quality assessment for fake biometric
detection: Application to iris, fingerprint, and face recognition. IEEE transactions on
image processing, 23(2), 710-724.
Irgens, P., Bader, C., Lé, T., Saxena, D., & Ababei, C. (2017). An efficient and cost effective
FPGA based implementation of the Viola-Jones face detection algorithm. HardwareX, 1,
68-75.
Jridi, M., & Alfalou, A. (2017, May). Rapid prototyping of SoC-based real-time vision system:
application to image preprocessing and face detection. In Pattern Recognition and
Tracking XXVIII (Vol. 10203, p. 102030M). International Society for Optics and
Photonics.
Lee, H. W., Peng, F. F., Lee, X. Y., Dai, H. N., & Zhu, Y. (2018, April). Research on face
detection under different lighting. In 2018 IEEE International Conference on Applied
System Invention (ICASI) (pp. 1145-1148). IEEE.

9FACE DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE
Simpson, E. A., Jakobsen, K. V., Damon, F., Suomi, S. J., Ferrari, P. F., & Paukner, A. (2017).
Face detection and the development of own‐species bias in infant macaques. Child
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Sparavigna, A. C. (2016). The Appearance of Roman Emperors Rendered by a Face Detection
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Zafeiriou, S., Zhang, C., & Zhang, Z. (2015). A survey on face detection in the wild: past,
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