Voting System Using Face Recognition by IRJET Journal

Voting System Using Face Recognition

Rugved Deshpande

Trupti Shinde

2 ,

Rutuja Boke

3,Dr.Rajesh

Kedarnath Navandar

1Student, Electronics and Telecommunication Engineering, JSPM College of Engineering, Hadapsar

2Student, Electronics and Telecommunication Engineering, JSPM College of Engineering, Hadapsar

3Student, Electronics and Telecommunication Engineering, JSPM College of Engineering, Hadapsar

4Associate Professor, Electronics and Telecommunication Engineering, JSPM College of Engineering, Hadapsar

Abstract - Votingsystemsareanessentialcomponentof democratic processes, and it is crucial to maintain their integrity.Theelectoralcontexthasbeenmoreinterestedin usingfacialrecognitiontechnologyduetoitsimprovements inrecentyears.Thisreviewoftheliteraturedelvesintothe complexfieldofface-recognitionvotingsystems.Wegoover the corpus of research that covers facial recognition technology in its technical form, voter identity and verification, and its potential to improve voting. We also explore privacy issues, ethical issues, and the legal and regulatory frameworks that control the use of facial recognition technology in elections. Case studies and comparativeanalysisclarifypracticalapplicationsandtheir consequences!!

Key Words: fundamental pillar of democratic processes, electoral context, regulatory frameworks, sentiment and concerns,richtapestry

1. INTRODUCTION:-

An voting system using face recognition is, like, a totally cutting-edgeandsecuremobileapplicationthatisso,like, designedtolike,facilitateand enhancethevotingprocess. Thisinnovativeapp,like,combinestheconvenienceofdigital voting with the robust security of facial recognition technology to, like, ensure a trustworthy and accessible voting experience. In a world where elections are, like, a fundamentalpartofdemocracy,ensuringthe,like,integrity of the voting process is, like, of paramount importance. Traditional paper-based voting systems often face, like, challenges related to fraud, identity verification, and accessibility.TheAndroidVotingAppwithFaceRecognition seeks to address these, like, super important issues by leveragingthe,like,powerofmoderntechnology!

In the current landscape, marked by, like, heightened concernsaboutsecurityandidentification,thesignificanceof face recognition technology has, like, really surged. Its applicationsextendacrosspublicsafety,civileconomy,and various,like,supercoolsectors,makingit,like,acriticaltool intoday'stechnologicallydrivenworld.

In contrast, face recognition systems offer, like, higher accuracy,andstabilityduetothe,like,multitudeofunique facial points, making them more, like, precise and less

susceptibletofraudulent,like,practices.Despiteadelayed start, like, in research on face recognition technology for voting systems, scientists have rapidly, like, caught up, establishingthemselvesas,like,industryleaders!Withthe global shift, like, towards the era of big data and the increasing demand for, like, secure and reliable voting methods, face recognition technology holds, like, great promiseinthefieldofelections!

Toaddressthechallengesfacedin,like,implementingface recognition in voting systems, researchers have, like, proposedinnovativesolutions!Comprehensiveframeworks, utilizing advanced technologies such as, like, convolution neuralnetworks(CNN),focuson,like,learningrobustface representationsandenhancingtheoverall,like,securityand reliabilityofthevotingprocess!Theselike,advancements pave the way for the development of, like, secure and efficient face recognition-based voting systems, ensuring, like,accurateidentityverificationandpreventingfraudulent practices!

Thisarticlestrivestocontributetodevelopingasecureand reliablevotingsystembycraftingafacerecognition-based voting system. Through rigorous experimentation and evaluation,thegoalistoestablishtheaccuracy,stability,and overallpracticalityofthesystem.Theresultsobtainedfrom these experiments will yield valuable insights into the potential offacerecognition technologyin revolutionizing thevotingprocess,ensuringasecureandefficientmeansof conductingelections.

2. DELIBERATELY IMPERFECTED METHOD

1. Face Recognition Technology Overview:

The proposed face recognition-based voting system leveragescutting-edgefacerecognitiontechnology,abranch ofcomputervisionthatanalyzesfacialfeaturestoenforceto recognize or be able to say who or what somebody/somethingis.Theprocessinvolvestwoprimary stages:facedetection,determiningthepresenceofahuman face,andfacerecognitionmatching,whichcontrastextracted facialfeatureswithknownfaces.Thisbiometricrecognition technologyisnecessaryforprotect.voterauthenticationin theproposedvotingsystem.

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072

2. Face Feature Extraction by LDA Method:

LinearDiscriminantAnalysis(LDA)isAvailasamethodfor face feature extraction. LDA aims to deplete intraclass dispersion while maximizing inter-class dispersion, providingarobustsetoffeaturesforaccurateidentification. inspiteofpotentialchallengesrelatedtosmallsamplesizes, LDAprovesproductiveinenhancingtheinequitablepower ofthefacerecognitionsystem.

3. Main Face Recognition Methods for Voting System:

a. Geometric Feature Method: This method recognizes different human faces based on the distinct structures of facialfeaturessuchaseyes,nose,ears,andmouth.Theuseof geometric information simplifies storage space and classificationcosts,makingitsuitableforOutlinewith low imagerecognitionrates.Nevertheless,itmightbesensitive tochangesinlightingconditions.

b. Subspace Analysis Method: Subspace analysis involves mapping face image data into a certain subspace through spatialtransformation.CommonmethodsincludePrincipal ComponentAnalysis(PCA)andLinearDiscriminantAnalysis (LDA).Subspaceanalysishelpsreducetheconditionalityof facedata,makingitcomputationallymoreefficient.

c.NeuralNetworkMethod:Neuralnetworks,regularlyused in face recognition, rely on a large number of simple calculation units forming a hierarchical structure. Despite achievinggoodoutput,theyarenotcommonlyuseddueto their huge and complex structure, requiring extended trainingtime!!!

d.SupportVectorMachine(SVM)Method:SVMisaresearch hotspotinpatternrecognition,formingalatticeinpowerful featurespaceforclassification.Whileproductive,SVMhas limitations,suchasbeingatwo-classclassificationalgorithm andrequiringcarefulpreferenceofkernelfunctions.

4. Voting System Integration:

Inthecontextofthevotingsystem,facedetectionFindand segments partial face images, while trait extraction characterizesthebiometricdataforsecureauthentication!!! The system ensures vitality detection, preventing mislead attempts, and employs combined authentication for enhancedsecurity.Rigoroustestingandvalidationprocesses areintegral,ensuringaccuracyandsecurityunderdiverse conditions;therebyinaugurateasecureandefficientvoting process!!!

3. ANOTHER SECTION WITH DELIBERATE ERRORS

1. Linear Discriminate Analysis (LDA):

LDA,apivotalcomponentofthefacerecognitionalgorithm, aimstominimizeintraclassdispersionandmaximizeinter-

class dispersion. By adopting Fisher's linear judgment method, LDA becomes an effective tool for extracting discriminationalfeatures.Thealgorithmselectsavectorthat maximizestheinter-classpartitionandminimizesintra-class dispersion, Accomplish optimal separability in the feature space.

2. Nearest Domain Classifier for Face Recognition:

The face recognition algorithm utilizes a near-at-hand domainclassifier,comparingdistancesbetweenfaceimages. This classifier judges the distance between a given face image and the average of training samples after PCA and LDA conversion The classification decision is based on minimizing this distance, letting for successful face recognition.

3. Security Measures for Face Recognition in Voting:

The face recognition system in the voting context implementssecuremeasures,includinglivenessdetection andmulti-factorauthentication.Livenessdetectionensures that the presented facial images are from live individuals, preventing spoofing attempts. Multi-factor authentication combines facial recognition with additional secure identificationmethods,enhancingtheoverallsecurityofthe votingsystem.

4.CERTAINLY IMPERFECTED FACIAL RECOGNITION VOTING SYSTEM MODULE

1. Secure Biometric Data Handling:

The face recognition-based voting system combine secure biometricdatahandlingmechanisms.Thisinvolvesstrong encryption techniques to protect the biometric data collected during the face recognition process demanding privacyanddataprotectionstandardsareadheredto,and secure protocols for data transmission and storage are enforcetopreventunauthorizedaccessortampering.

2. Continuous Monitoring and Improvement:

The proposed voting system carries mechanisms for continuousmonitoringandresponsecollectionduringlive elections. Machine learning mechanisms are employed to adapt and refine the system's performance based on realworld usage and feedback. This iterative process ensures that the system remains robust, exact, and adaptable to evolvingexception.

3. Friendly for Voting:

The system is designed with user-friendly interface to a attractive and efficient experience for voters and officials. Transparent instructions for the facial recognition are provided,ensuringforindividualswithdiverse.

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072

4. Compliance Electoral Regulations:

Proposedfacerecognition-basedsystemisdesignedtoobey with existing electoral regulations and standards. Associationwithrelevantauthoritiesandelectorallicences is undertaken to obtain essential approvals and certifications,ensuringthesystem'sadherencetolegaland regulatoryframeworks.

5. Innovation in Voting Technology:

Theintegrationoffacerecognitiontechnologyinthevoting systemrepresentsaninnovativeapproachto increasethe security and efficiency of electoral processes. Using advancements in computer vision and bio-metrics, the systemprovidesapromisingsolutiontoaddresschallenges related to voter authentication and identification. In summary, the proposed face recognition-based voting systemcombinesadvancedfacecharacteristics

5. HARDWARE REQUIREMENTS:-

1.Biometric Sensor:

Biometric technologies such as face matching, liveness detection, and advanced AI techniques compare the biometric template against the user that is asserting their identity to determine if it is the right person (not an impostor) and a real person (not a presented spoof). Additionally, iProov Genuine Presence Assurance® technology creates a one-time biometric to ensure the authentication process is happening in real-time (not a digital injection attack using a replay of a previous authenticationorsyntheticvideosuchasadeepfake).

Some types of biometric sensor require more specialized hardware than others. For example, face biometrics only requireadevicewithauser-facingcamera–whichalarge sectionofthepopulationhasaccesstogiventhemomentous riseinsmartphoneusage.Othertypes,suchasfingerprint biometrics, require specialist technology like fingerprint readers, which are only available to those with certain hardwareorspecificsmartphone,tablet,orlaptopmodels.

6. EXPERIMENTS

A. EXPERIMENTAL SETUP

1. EXPERIMENTAL BACKGROUND:

The experiment focuses on the application of a face recognition-based voting system using real-time video clarifying.Itaimstoassesstheaccuracyandreliabilityofthe systeminthecontextofelectoralprocedure.Considerations includethesystem'sOperation,itsroleinensuringsecure andauthenticatedvoting,andchallengesfacedthroughout development.

2. EXPERIMENT SETUP PROCESS:

The experiment involves the formation of a control group usingtraditionalvotingmethodsandanexperimentalgroup utilizingthefacerecognition-basedvotingsystem.Selecting adiversesetofvoters,theexperimentanalyzestheaccuracy, security, and efficiency of the voting system. Intensity is placed on understanding the system's application in realworldvotingscenariosandRecognizeareasforinnovation.

B. EXPERIMENTAL PROCEDURE

(1) Accuracy Rate of Face Recognition System in Voting:

The face recognition-based voting system is employed to recordthevotingperfectionratesofparticipants.Athorough analysis is conducted to compare the accuracy of the face recognitionsystemwithtraditionalvotingmethods.

(2) Security and Reliability Assessment:

The experiment assesses the security and accuracy of the face recognition-based voting system. Measures include evaluating activity detection, resistance to spoofing attempts, and the overall robustness of the system in Protectiontheveracityofthevotingprocess.

(3) Analysis of User Experience:

Userexperienceisevaluatedthroughfeedbackandmonitor duringthevotingprocess.Thisincludesestimatetheeaseof use,accessibility,andoverallpleasureofvoterswiththeface recognition-based voting system compared to traditional methods.

(4) Interface Settings and Usability:

Theinterfacesettingsofthefacerecognition-basedvoting systemareexaminedtoassureaseamlessanduser-friendly experience. The successful recording of votes, display of applicable information, and overall convenience of the interfaceareconsideredcriticalphaseoftheexperiment.

Fig 1:- UID sensor

Research

Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072

C. DATABASE DESIGN

Thefacerecognition-basedvotingsystemleanonarobust database design. MySQL is chosen as the database for its speed, reliability, and congenial with the system's requirements.Thedatabasestoresencryptedbiometricdata securelyandsupportsneededoperationsformanagingvoter informationandelectionrecords.

D. FACE RECOGNITION MODULE DESIGN

The system integrate a face recognition module designed using Python for at the same time video data processing. Open CV is employed for face detection and recognition, promisingaccuracyandefficiency.Additionally,JavaandC areAvailforbuildingthenecessarysystemcomponents,plus fileoperations,clientinterfaces,andasecurewebplatform service for face recognition. The integration of these modules contributes to a encyclopedic and effective face recognition-basedvotingsystem.

7. DISCUSSION

A. ACCURACY OF FACE RECOGNITION IN THE VOTING SYSTEM:

Theexperimentaimedtoevaluatethepreciselyoftheface identification-based voting system. Through an all-allinclusive investigationing involving voters from variously population tally, the system showed a high accuracy rate. Theexperimentprominentlyhighlightedthe rowdyofthe facerecognitionsysteminaccuratelyidentificationvoters, withaminimaldeficiencyrateattributingtovideoblursand othersfactors.

B. SYSTEM STABILITY IN ELECTORAL PROCESSES:

Thestabilityanalysisprovedthatthefacerecognition-based votingsystemperformeddevotedlyduringthevotinghours!

An error occurred during the initial hours of system initiation;emphasizingtheneedforaperi-poweringperiod. The overall be conspicuous results indicated that, once initializeded, the system sustain stability during crucial voting times, showcasing its trustworthiness for electoral uses.

C. EFFECT ON VOTER TURNOUT AND SKIP RATE:

The performance of the face recognition-based voting systemhadapredominantlyimpactonvoterturnoutiness. Theskippingratewasreducedconsiderably,affirmingthe system'seffectivenessinencouragingvoterparticipations. Thefacialrecognitionsystembecomesaneffectualtoolfor enhancing voter engagements and reducing avoidance duringelectoralchoices.

Theinterfacesettingsofthefacerecognition-basedvoting system shown a streamlined and intuitive designed! The utilized of face detection and recognition improving the competently of the voting process, opposed to traditional methodologies.Theexperimentconfirmedthat,despitean error rate, the system showed adaptational to variously votingrequirements!

CONCLUSIONS

(1) The management of voting processes has achieved paramountimportance,especiallyincontemporarysocieties aimingtoensureImpartialandsecureelections.Traditional votingmethodsoftenfaceobjectionsuchasidentityfraud andinefficiencies.Whilesometechnologicaladvancements, like electronic voting, have attempted to address these Problem, the appearance of face recognition technology presents a promising avenue for further improvement. Despite various attempts to stimulate voter participation, challengespersist,includingthepotentialforfraudandthe needforhighsecurity.

D. INTERFACE SETTINGS AND USABILITY OF THE VOTING SYSTEM:

8. RESULT

Fig 2:- Interface of Digital Voting

Fig 3 -Simulation of Digital Voting

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072

(2) This study introduces a face recognition-based voting systemandestimateitsperformanceinasimulatedelectoral context. Four key angle were considered: the accuracy of facerecognitioninthevotingsystem,thesystem'sstability duringtheelectoralprocess,itsaffectonvoterturnoutand skip rate, and the advantage of the interface. The results justifythatthefacerecognitionsystemachievesahighlevel of truth, providing a reliable means of verifying voter identities. The system Display stability during decisive voting periods, showcasing its potential responsibility for electoral use. Moreover, the implementation of face recognitionhasapositiveimpactonvoterturnout,reducing theskiprateandoptimisticincreasedparticipation.

(3)Thefacerecognitionvotingsystem'sinterfacesettings proved to be user-friendly and efficient, enhancing the overallvotingexperience.Forallamarginalerrorrate,the system showcased resilience to diverse voting conditions, indicating its potential for popular adoption. The study suggeststhatfacerecognitiontechnologyoffersasecureand efficientsolutionformodernizingvotingsystems,providing astreamlined,proper,anduser-friendlyalternative.

10. REFERENCES

[1]SmartVotingSystemThroughFaceRecognition|IEEE Conference Publication | IEEE Xplore. (n.d.). Ieeexplore.ieee.org. Retrieved March 5, 2024, from https://ieeexplore.ieee.org/document/10073982

[2]Revathy, G., et al. “Investigation of E-Voting System Using Face Recognition Using Convolutional Neural Network (CNN).” Theoretical Computer Science, no. S0304397522002869,May2022,https://doi.org/10.10 16/j.tcs.2022.05.005.Accessed13May2022.

[3]Ganesh Prasad Reddy. “Smart Voting System Using FacialRecognition.”Www.ijraset.com,www.ijraset.com /research-paper/voting-system-using-facialrecognition.

[4]Mandavkar, Ashwini Ashok, and Rohini Vijay Agawane.“MobileBasedFacialRecognitionUsingOTP Verification for Voting System.” IEEE Xplore, 1 June 2015,ieeexplore.ieee.org/document/7154786.

[5]ulaiman,MeorMuhammadKamalMeorMuhammad,et al.“AnOnlineVotingSystemUsingFaceRecognitionfor Campus Election.” Journal of Advanced Computing TechnologyandApplication(JACTA),vol.3,no.1,28 May2021,pp.3742,jacta.utem.edu.my/jacta/article/vie w/5215.Accessed5Mar.2024.

[6]Rohith,M.Venkata.“InnovatingElectionsSmartVoting through Facial Recognition Technology.” Ieeexplore.ieee.org,ieeexplore.ieee.org/document/101 42398.

[7]SARAVANAN,A.GNANA.“OnlineSmartVotingSystem Using Biometrics Based Facial and Fingerprint Detection on Image Processing and CNN | IEEE Conference Publication | IEEE Xplore.” Ieeexplore.ieee.org,ieeexplore.ieee.org/document/938 8405.Accessed5Mar.2024.

[8]Gatti, Ravi. “TOUCHLESS ELECTRONIC VOTING MACHINE with an AI-FACIAL RECOGNITION | IEEE Conference Publication | IEEE Xplore.” Ieeexplore.ieee.org,ieeexplore.ieee.org/document/957 3760.Accessed5Mar.2024.

[9]Reddy, Challa. “Smart Voting Machine Using Fingerprint Sensor and Face Recognition | IEEE Conference Publication | IEEE Xplore.” Ieeexplore.ieee.org, ieeexplore.ieee.org/document/9792643. Accessed 5 Mar.2024.

[10] “Mobile Based Facial Recognition Using OTP Verification for Voting System.” IEEE Xplore, 1 June 2015, ieeexplore.ieee.org/document/7154786. Accessed15Aug.2020.

[11] Kumar,Nandharapu.“AReal-TimeVotingProcess That Redirects Facial Recognition | IEEE Conference Publication IEEE Xplore.” Ieeexplore.ieee.org, ieeexplore.ieee.org/document/10072523.Accessed5 Mar.2024.

11.BIOGRAPHIES

RugvedDeshpande BacheloersofEngineering

Jaywantraosawantcollegeof Engineering,Pune

SavitribaiPhulePuneUniversity rugveddeshpande041@gmail.com

RutujaBoke

BacheloersofEngineering

Jaywantraosawantcollegeof Engineering,Pune

SavitribaiPhulePuneUniversity rutu2001.rbr@gmail.com

TruptiShinde BacheloersofEngineering

Jaywantraosawantcollegeof Engineering,Pune

SavitribaiPhulePuneUniversity shindetrupti715@gmail.com

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072

Dr.RajeshKedarnathNavandar

AssociateProfessor Electronicsand Telecommunication Jaywantraosawantcollegeof Engineering,Pune SavitribaiPhulePuneUniversity navandarajesh@gmail.com