Department of Electrical and Computer Engineering (ECE)

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https://repository.northsouth.edu/handle/123456789/10

In 1993, during the founding of North South University, the first private university of Bangladesh, the department was established in the name of Department of Computer Science. Since its inception it has gone through many transformations and transitions. The department continued with the same name till 2006 when it was renamed as Department of Computer Science & Engineering (CSE) as it had been offering Computer Engineering program from Spring 2003. As the number of students was growing and the demand for Electrical and Electronic Engineering was creating, the department started offering BS in Electrical and Electronic Engineering (EEE) degree from Spring 2009 and the department was renamed again as Department of Electrical Engineering and Computer Science (EECS) in that same year. Later on it was renamed again as the Department of Electrical and Computer Engineering (ECE) in 2014.

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Open Access
3D Multiplayer First Person Shooter Game
(North South University, 2019-08-31) Samira Mahmood; Maruf Ahmed; Nafisa Mahbub Piyal; Md. Hayder Ali; AKM Bahalul Haque; 1520265042; 152 0054 042; 152 1230 642; 152 1231 642
Video Games have always been a leading form of entertainment being available for people of all ages. Eventually, with the evolution of technologies improving the functionality of playing video games, multiplayer games have received increased popularity. In a multiplayer game, several people interact in real-time over a network like internet or a local connection. One of the primary reasons for multiplayer games receiving so much enthusiasm and attention is because of the thrilling experience of competing with human counterparts. Over the years, Bangladesh has become a significant part of the gaming community, yet there aren‘t many startups or individuals who are seeking to get involved in the lucrative game industry. In reference to the aforementioned facts and enormous popularity of multiplayer games, our incentive is to contribute and to be part of the global game industry. We plan to create a 3D multiplayer FPS (First Person Shooter) game with appealing graphics and visuals, and we‘ll also include some features to make the game stand out
Embargo
A CLOUD BASED MICROPAYMENTS SYSTEM FOR E-COMMERCE PURCHASES: SECURED USING FINGERPRINT AUTHENTICATION AND ENCRYPTION.
(North South University, 2019) Tahmid Khan Nafee; Zubair Rahman; Fariha Islam; Sadman Mahmud; Zunayeed Bin Zahir; 1430312040; 1430133042; 1530704042; 1530948042
Online payments are a big pain point in Bangladesh, especially in the context of the rapidly growing e-commerce industry. Most people don't have easy access to credit cards, due to the increasing fear of money laundering and theft. Moreover, even when credit cards are issued, there is a significant monthly cap, which hinders the industry. In this report, a solution in the form of a mobile payments system is presented. The customers are able to deposit money into their accounts as easily as re-charging their cell phone plans and the merchants are able to accept payments from these customers through secure generation of invoices. Therefore, with certain assertion it can be stated that steps have been taken in the right direction to actually solve the problem of online payments in Bangladesh.
Open Access
A Multichannel Localization Method for Camouflaged Object Detection
(North South University, 2022) Mohammad Rakibur Rahman; Md Mafri Chowdhury; Md Shohanur Rahaman Sarker; Md Shahriar Karim; 1812964042; 1813393402; 1812457402
Camouflaged objects can be difficult to detect because they blend in with their surroundings. There have been numerous studies on detecting camouflaged objects, and many of these have been recognized as effective approaches. This paper presents a new algorithm for detecting camouflaged objects by focusing on identifying the region of interest, which is crucial for detecting these objects. The algorithm uses Phase Fourier Transformation to create a filtered image, and Entropy to generate a feature map from the filtered image. The feature map is then used to determine the region of interest. This paper proposes a multichannel method for discriminative region localization in Camouflaged Object Detection (COD) tasks. In one channel, processing the phase and amplitude of a 2-D Fourier spectrum generates modified form of the original image, used later for a pixel-wise optimal local entropy analysis. The other channel implements a class activation map (CAM) and Global Average Pooling (GAP) for object localization. We combine the channels linearly to form the final localized version of the COD images. Experimentation in multiple COD datasets demonstrates that the proposed method successfully localizes regions containing more than 80% of the camouflaged objects. Our proposed method does not require memoryintensive devices or prior training on particular image features, making it easily integrated into a resource-constrained environment. Theproposed approach is also applicable to non-COD images
Open Access
A solution for industrial problem: Predicting the future market price using low amount of data with the help of Time Series Analysis
(North South University, 2019) Istiak Rahman; Zareen Tasnim; Farzeen Ahmed Bashori; Mahdy Rahman Chowdhury; 1530861642; 1511908042; 1510223642
Bangladesh has a lot of potentialities and possibilities as a third world country if it utilizes the blessings of technology properly. With the help of recent technology, different time series analysis models have been developed like ARIMA, ARIMAX, SARIMA, SARIMAX, and even a Facebook developed module called Prophet. Nowadays it is possible to detect the future trend of any business given any type of data. We have applied a similar approach to predict sales for one of the flourishing startups of the country named Rokomari.com. The struggle for any company is to sustain amongst its powerful competitors in its emerging years. It becomes easier to ace over the competitors if the company can have a prior preparation of its upcoming challenges. Our effort was to make the journey smoother so that it can sustain in building a flourishing business amongst its competitors. In order to do so, we have worked with “real world” sparse dataset of the company itself. We were successful in predicting their possible sales for coming years using time series models like SARIMA and Fb Prophet. The paper discuses briefly about the significance and possibilities created due to implementation of our custom build software.
Open Access
A Web Service Based on API from where People can get blood in emergency situation
(North South University, 2022-01-01) Ashfi Mehenaz; Sajid Ul Alam; Md Meraj Hasan; Dr. Mohammad Ashrafuzzaman Khan; 1812002042; 1812347042; 1812577042
Our main purpose of this project is to help the people . Basically our project is health oriented and random people would be benefited using this web service named Blood Bank. Before implementing this idea we went through various types of research to check if there were any sort of web service available similar to our idea and we found some web service but we want to implement it in a different pattern so that general people can use it without facing any problem. Suppose, if there is any emergency and anyone needs a necessary group of blood then they can get the necessary information regarding the blood donor and according to their requirement’s they can contact each other through this web service. In the frontend part of our web service we are using html, css, javascript. In the backend part we are using Django. For the documentation and testing we are using Swagger. We are using sqlite for our database and for API’s we are implementing in Restful API. Through the building process of this website, we have to undergo different types of research to make our system even more helpful and easier to access for the general people. We faced several difficulties when we started to implement this because some things were not possible as we intended then tried different ways to solve those problems following comparatively easy procedures. And finally, we are able to make this web service as we desire.
Open Access
Agriculture Monitoring Rover
(North South University, 2019-12-31) Samiul Azim; Md. Moniruzzaman; Dr. Shazzad Hossain; 1531403042; 1511198042
Bangladesh economy draws its main strength from the agriculture sector. The sector contributes 19.10% to GDP (at current prices) and employs 50.28% of the labour force.1 However inadequate management practices (fertilizer, water, and pests & diseases) are one of the driving causes for agricultural productivity to be reduce din Bangladesh. The use of fertilizers, quality seeds, and irrigation together cannot ensure sustainable production unless timely and appropriate measures for the management of other nutrients are simultaneously pursued. Therefore this project proposes a completely innovative, user friendly technology that assists farmers in maintaining their crop nutrients without any effort. The function of the rover will be to move around a field comprised of a fixed area. This will be established using a GPS tracker. The rover will it have a colour sensor, DHT sensor, water sensor, moisture sensor which will detect the colour change, and also other things which affect the crop’s growth and wellbeing. The information collected by the rover will be sent to the farmers via a message over their personal mobile phones. Our project aims to give actual data or condition of the crops to the producers to take right steps for the yield production. Using these information, the farmer can take necessary steps for the well- being of the crops, further improving crop yield and productivity
Open Access
An Autonomous Surveillance Drone
(North South University, 2019) Md. Jobayer Hossain Sourav; Adnan Islam; M Asif Ibna Azad; Mohammad Al-Amin Hossain; Mirza Mohammad Lutfe Elahi; 1430578042; 1430575042; 1430366042; 1420212042
Drones have become very common these days in the entertainment field. People use drones to take amazing videos and pictures of landscapes. We have used this entertainment device in a more helpful way with which we can solve real world problems. Our drone has features such as surveillance, object detection and crowd detection. The main idea of our project is aimed to ensure precise and fast surveillance throughout a specified area using autonomous surveillance. It is aimed to be used for violence detection, law breakers and any other objection that pose a threat to the law. It scans all the places that CCTV cameras cannot cover and reports back live video feedback to the security personnel. Our work mainly aims to improve surveillance technologies and shape a secure compound. With the rise in security issues in the past decade, many people have resorted into unfair means of conduct. Also, with the rise of technology, it has become easier for law breakers to plan about an event without any security officials knowing about it. CCTV cameras are sometimes able to catch the intruders but, in most cases, due to the angle in which the camera is set to, many crimes go unnoticed. Our drone can detect any unwanted object or unauthorized person inside a given territory. Moreover, if there is any crowd which can pose a threat for the security concern, our drone can autonomously detect the crowd and send notification to the nearby security personnel.
Open Access
Assistive App for Visually Impaired People
(North South University, 2023) Arham Chowdhury; Tasnuva Nawar; Saifuzzaman; Sumiya Sultana; Shahnewaz Siddique; 1931861642; 1931816642; 1931406042; 1931277642
Monetary transactions are an indispensable part of our day to day activities. In case of a large amount of cash transaction, human error is a matter of concern. Thus the need for an efficient automated system for currency recognition has become significant these days. The challenge of currency recognition and object detection remains a significant obstacle for individuals with visual impairments. This issue is particularly pronounced in developing nations, where robust currency recognition systems are scarce. Recent research efforts have sought to address this issue, focusing on the complexities posed by the gradual degradation of currency notes over time. Recognizing currency notes has become increasingly complex due to wear and tear. Notably, the development of currency recognition systems adjust to the needs of visually impaired individuals in Asian countries has been relatively limited. To address this challenge, research has been conducted, leading to the forthcoming implementation of a practical application featuring two core components: an Image Classification Module and a Text-toSpeech Module. The primary hurdle in both modules is to enhance accuracy by using deep learning techniques. This initiative represents a crucial step in improving accessibility for visually impaired individuals, especially in regions with limited resources. The trained deep learning model achieved a remarkable 91% accuracy, indicating the convergence of the model during the validation process. This outcome signifies a significant advancement in providing accurate and reliable currency recognition and object detection for visually impaired users
Open Access
Automated Fisheries Water Quality Monitoring System
(North South University, 2020-04-30) Tanbin Akter Mitaly; Paplu Dash; Md. Shahriar Hussain; 1712438642; 1611420043
Fisheries is one of the main prospects to grow economically also we benefit from it by the production of food and the nutrition that is required us to live by. For fisheries, it's important to maintain good water quality as it is an important factor that affects fish health and performance in the aquaculture production system. It matters what type of fish we are culturing in our system due to different fish species need a different range of water quality aspects in which they can survive. Different fish species have a different optimized point to growing well. Don't maintain the water quality can result in parasite infestations, poor growth, erratic behaviour and various disease system. The water quality is dependent on climate, seasonal changes also how a culture system is used. To maintain good water quality conditions we need to look at physical and chemical components of water that have an impact on water quality.
Open Access
Automated Hydroponic System Using IOT and Cloud Computing
(North South University, 2019) Ramiza Maliha; Md. Nahid Rahman Ontu; Syed Tahmid Abra; Zunayeed Bin Zahir; 1430592042; 1431123042; 1430651042
In this report, we have explored the idea of automation in regards of hydroponic system. The purpose of this project was to make this process more manageable and accessible for the masses so that the people of Bangladesh can re-establish the slowly falling agricultural sector with advance new technology. As the unemployment rate is increasing and people are looking for new ways to stabilize the growing economy that people of Bangladesh has worked hard for, the most lucrative offer can come from the most back dated sector of our country, thus the hydroponic system. Hydroponic system can be the emancipator of our agricultural system, albeit the venture is quite risky due to the fact that we lack both knowledge and resources. Since, hydroponic system present itself as something of a sacrilege, which more often than not, people tends to avoid. Furthermore, with the backward technology we have mixed with the lack of understanding, most of the enthusiast either gives up half way or are still struggling. Ergo, this project is aiming to help the entrepreneurs to invest in agriculture so that we can not only reinvent our agriculture sector with new generation of young people, but also provide the country with adequate food, medicinal plant, foreign plants etc. We are integrating internet of things (IoT) and cloud computing to ease the hydroponic system, which requires constant maintenance, so that the new comers has more access.
Open Access
CarKoto Bangladesh Used Car Buy And Sell Platform And Price Prediction Using Machine Learning.
(North South University, 2023) Sabrina Jahan Akhi; Abdullah Nafis Chowdhury; Sayem Ahmed Sajil; Mohammad Abdul Qayum; 1821164042; 1921081042; 1921449642
This project has two parts in it. One part is a website for selling vehi cle and the other part is machine learning which will predict the price of the vehicle.For user input we will be taking car name, car model, model year, brand, registration year, cc, car type, car price.The main ideology of this project is using a machine learning model that will predict the price of the vehicle provided that we give some infor mation about the vehicle details to the system and the system will predict the appropriate price for that specific vehicle. This will help customers to get an idea before they go for purchasing a vehicle. This will help both the seller and buyer. The seller will get the appropriate value for his/her vehicle and the buyer will also get the best vehicle at his/her price.This will also reduce any kind of mis guidance or fraudulence or scamming during the purchase. So we can say this is a safe platform for buying and selling used vehicles.
Open Access
Comparative Analysis of Multi-disease Prediction using Deep learning
(North South University, 2023) MD. Mehedi Hasan Bhuiyan Nipu; Md. Raihan Uddin Sarker; Meherin Afroz Mime; Ahanaf Akif Parvez; K. M. A. SALAM; 1911870042; 1912115042; 1912965642; 1821145042
This study focuses on the development and deployment of a multi-disease prediction system utilizing deep learning algorithms applied to MRI brain images. The research involves the creation of a specialized network model trained on MRI datasets collected from Kaggle, aimed at predicting various neurological conditions. The proposed model's architecture involves convolutional layers extracting intricate features from the MRI images, transitioning from raw data to pixel-level details, edges, shapes, and finally, disease-relevant regions. Visualization techniques highlight the extracted features and emphasize the network's ability to differentiate between healthy and diseased brain structures. Moreover, the study elucidates the interpretability of the CNN model through weight visualization and modified fully connected layers, delineating distinctions between classes, such as healthy controls and patients with Parkinson's disease. The performance evaluation of multiple deep learning models, including Basic CNN, Modified CNN, AlexNet, and VGG16, is conducted across various epochs. Results showcase notable accuracies in predicting Brain Stroke, Parkinson's disease, and Alzheimer's disease, with each model exhibiting distinct performance metrics. For instance, in Parkinson's disease prediction, transfer learning with VGG16 attains an accuracy of 98.79%, while Basic CNN achieves 91.984% accuracy in Brain Stroke prediction. This comparative analysis highlights the efficiency of deep learning methodologies in diagnosing neurological conditions using MRI data. The findings underscore the potential of these models in facilitating accurate disease identification, paving the way for improved diagnostic tools and interventions in neurology.
Open Access
CPPS: A portal for tracking and guiding algorithmic problem solvers
(North South University, 2019) Abdullah Al Imam; Labib Md. Rashid; Hasib Al Muhaimin; M Shazzad Hosain; 1511013042; 1510712042; 1510720042
Sport programming is a fairly underrated co-curricular activity for students of various levels. It can be a very productive hobby for professionals as well. Regular involvement with programming problem solving keeps a programmer’s skill to write code from scratch fresh and gives various perspectives in approaching problems of different fields of Computer Science and Software Development. Universities all over the world take initiatives and run training programs for developing highly skilled competitive programmers. This project acknowledges the need for smoothening the process of training students for competitive algorithmic problem solving. The end result of this project is a Web application serving programmers, helping to improve their problem solving skill. It also serves trainers for managing and guiding their students. This app provides with a very well defined guideline and tools for programmers to pursue their goal of becoming a highly skilled programmer and enables them to do well in programming contests as well as building their career as a computer science professional.programming is a fairly underrated co-curricular activity for students of various levels. It can be a very productive hobby for professionals as well. Regular involvement with programming problem solving keeps a programmer’s skill to write code from scratch fresh and gives various perspectives in approaching problems of different fields of Computer Science and Software Development. Universities all over the world take initiatives and run training programs for developing highly skilled competitive programmers. This project acknowledges the need for smoothening the process of training students for competitive algorithmic problem solving. The end result of this project is a Web application serving programmers, helping to improve their problem solving skill. It also serves trainers for managing and guiding their students. This app provides with a very well defined guideline and tools for programmers to pursue their goal of becoming a highly skilled programmer and enables them to do well in programming contests as well as building their career as a computer science professional.
Open Access
Deep Learning Approach for Keypoint-Based Bangla Word Sign Detection for Videos
(North South University, 2023) Arnop Singh Durjoy; MD. Shahidul Islam; Mahidul Islam Bhuiyan; Atiqur Rahman; 2011061042; 2011703642; 2011111642
This research delves into the realm of Bangla sign language recognition, focusing on developing a robust system for interpreting and analyzing gestures depicted in videos. Employing a keypoint based approach and leveraging deep learning technology, specifically a two-layer LSTM architecture, our methodology aims to interpret Bangla word signs accurately. The project's foundation lies in a meticulously curated custom dataset featuring 51 unique signs captured by two proficient signers, ensuring comprehensive coverage of articulation, speed, and style variations. Our system's tailored approach acknowledges a bridge to communication gaps and enhances accessibility for the Bangla-speaking Deaf community. Beyond technical advancements, this research aims to elevate societal awareness and foster employment opportunities for the Deaf population, ultimately contributing to a more inclusive world. The outcomes of this project have the potential to not only revolutionize Bangla sign language recognition but also pave the way for broader applications in accessibility and advancements in deep learning technology for diverse sign languages worldwide.
Open Access
Design and Investigation of Energy Harvesting System from Noise.
(North South University, 2021) Junayed Hossain; Nazmus Sadad Ovi; Mohammad Monirujjaman Khan; 1612680643; 1331388043
Human activity and various activities are needed to live in today's world, and all of these activities create different types of sound. A noise is a noisy or irritating sound that causes disruption, such as street traffic noises, construction sounds, airports, and so on. This paper looks at a less well-known renewable energy source. Using a suitable transducer, noise (sound) energy can be transformed into a viable source of electric power. This can be accomplished by using a transducer to transform noise-induced vibrations into electrical energy. Reducing the strain on the main power grid and reducing fossil fuel imports. A speaker and a transformer are used to convert noise generated by car horns and other noise sources into electrical energy in a proposed application. The theory of electromagnetic induction can be used to transform noise vibrations into electrical energy. A transformer was used to boost the received signal from 0.7 to 2 volts.
Embargo
Design of a low voltage digital thermostat using LM35 and PIC Microcontroller
(North South University, 2013) Kaiser Alam; K. M. A. Salam; 072163045
This system is about the design of a low cost temperature sensing and control system (thermostat) with the use of PIC microcontroller and LM35 temperature sensor. The system is relatively inexpensive to make and can be integrated with temperature control systems such as air conditioners and fans. Apart from making temperature control systems more affordable for everyone, this system also helps save energy by automatically switching the devices on or off at the appropriate temperatures. In this project the LM35 and PIC16f877a microcontroller have been used to make a digital thermostat that is programmed to switch on and off a fan automatically when the temperature rises above or falls below a certain threshold value. The device also includes a LCD display to indicate the ambient temperature to the user. The threshold temperature can be programmed into the PIC microcontroller using a PIC programmer. The device as a whole works as a digital thermostat. Commercially available digital thermostats work at 24V AC typically. Some versions use a low voltage as low as 6V or as high as 30V. In this project the thermostat design allows it to operate at only 5V, making it more energy efficient than currently commercially available digital thermostats. The versatility of the system allows it to integrate with many different devices. Apart from air conditioners, furnaces and fans, this system can be used to build incubators or to maintain a constant temperature in your refrigerator at home.
Open Access
Early Detection of Mental Health over Social Media Using Machine Learning
(North South University, 2020) Sabbir Hasan; Md. Tashfiq H. Choudhury; Md. Shahriar Karim; 1411107042; 1611508042
In this project, we have worked on the use of machine learning algorithms that may indicate the mental state or sentiment of the users of social media. The current linguistic research on tweets or statuses shows distinct language patterns talks much about the sentiments of the users. As such, we are encouraged to use the available social media dataset repository for performance analysis of the supervised learning models generally applied in the case of large datasets. We have captured the texts and preprocessed the text data using Python tools for feature selection that provides clues to sentiment and subsequently, the subjective sentences are classified as positive or negative. We built machine learning (ML) models out of the classified text features for random forest and LSTM algorithms. The accuracy of the classification in both cases is encouraging, particularly the LSTM algorithm. The whole work is carried out using rich libraries of Python machine language modules. A prototype web application is developed with a front end (input and output) and back end (ML models and classification) using a rapid prototype web application framework for testing the algorithms that enable us to check the mental status of a social media user to determine if they may require medical or emotional support. Social media emerges as the most critical source of information, reflecting people's expressions and communication through textual content. This work contributes to the application of machine learning to further enhance the early detection of the mental health of users.
Open Access
Energy-Entanglement Relation For Minimal QET Model Using Superconducting Quantum Computers
(North South University, 2023) Tasin Towsif Rahman; Sibghat Ullah Rayyan Shaikh; Monem Shahriar Sourav; Mahdy Rahman Chowdhury; 1911774042; 1831773042; 1831379042
In the easiest terms possible, quantum entanglement means that two particles are together in such a way that the actions of one particle affect or cause changes to the other particle no matter the distance between the two particles. These particles could be photons, electrons, etc, and the state that they exist in could be, for example, one particle ‘spinning’ in one direction and the other spinning in the opposite direction. For our experiment, we consider two particles Alice and Bob. The goal of our study is to investigate the degree of breakdown of entanglement between the two for the minimal Quantum Energy Teleportation (QET) Model, during energy teleportation. Entropy is used as a quantitative measure of entanglement. The measurements in the circuit destroy the entanglement that exists between the two qubits when energy is transmitted from "Alice" to "Bob" in the Quantum Energy Teleportation (QET) Model. As a consequence, we use entropy to show the extent of degeneration in the entanglement; in other words, we present two disparities in the amount of transmitted energy and the entanglement expenditure. We investigate entanglement as a quantifiable physical resource in connection to energy in this experiment.
Open Access
Enhanced Third Harmonic Generation (THG) with Graphite Metasurface
(North South University, 2023) Ybtida Cinderella; Nasim Md Arafat Saikat; Mahdy Rahman Chowdhury; 1921957043; 1911471643
This project introduces an innovative concept for improving third harmonic generation (THG) at far infrared and terahertz (THz) frequencies by employing ultrathin nonlinear meta surface designs of patterned graphite micro-ribbons. By utilizing the localized plasmonic effects, these configurations make it possible to produce an incident wave that is tightly confined and significantly amplified along the surface of the graphite. Because of the presence of a metallic substrate beneath the graphite micro ribbons, the resonant response bandwidth is reduced, which leads to the absence of any transmission and the development of standing waves within the intermediate dielectric spacer layer. This strategy results in a significant increase in the efficiency with which THGs are converted, one that could be increased by several orders of magnitude. Additionally, the meta surface's resonant frequency can be dynamically modified by changing the Fermi energy of the graphite through either electrical or chemical doping. This can be done to get the desired effect. The stimulation of highly localized plasmons within graphite micro-ribbons are the primary topic of this paper. This stimulation ultimately results in the confinement and intensification of the incident wave along the graphite surface. In addition, the presence of a metallic substrate beneath the graphite micro ribbons results in the induction of zero transmission and the generation of standing waves within the intermediate dielectric spacer layer, which together have the effect of narrowing the bandwidth of the resonant response. In the end, these improvements in the incident field contribute greatly to the gain in the efficiency with which THGs are converted.
Open Access
Face Recognition LogIn System
(North South University, 2022) Md. Ibrahim Khalil Ullah; Md. Mehraj Uddin; Oali Ullah; Md. Abu Obaidah; 1812015042; 1813213643; 1612545042
We can identify human faces using a web camera which is known as Face Detection. This is a very effective technique in computer technology. There are used different types of attendance systems such as log in with the password, punch card, fingerprint, etc. With rapid growth in the application of AI, Access Control Systems are walking in a new technology lane. Powered by deep learning technologies or cognitive analytics, login pages can implement more secure, efficient, and easy to use authentication systems. In this project, we have introduced a Facial Recognition type LogIn System that can identify a specific face by analyzing and comparing patterns of a digital image. This system is the Tensorflow LogIn System based on face detection. Primarily, the device captures the face images and stores the captured images into the specific path of the computer relating the information into a database. When anybody tries to enter into any website through this LogIn System, the system captures the image of that particular person and matches the image with the stored image. If this image matches with the stored image then the system allows the person to enter the website, otherwise the system denies entry.

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