Facial Recognition Based Attendance System

International Research

Facial Recognition Based Attendance System

***

Abstract - A This paper attemptstointegrateNodeMCU. It might be quite time-consuming for the teachers to manually manage attendance. To solve this problem, sophisticated and automatic attendance management systems are being deployed. The problem of proxies and students being counted as present even if they are not is easily resolved with this architecture. This technique recordsattendanceviaalivevideo broadcast. The video frames are extracted using OpenCV. The two main implementation tasks for this kind of system are face detection and face recognition. Following this, a relationship between them ought to be conceivable by comparing the identified faces with the database ofstudents'faces.Thismodel will be a useful tool for controlling staff and student attendance.

Key Words: Node MCU, Attendance, OpenCV, Database

1. INTRODUCTION

Human faces play a significant role in our daily lives, particularlywhenitcomestoidentification.Facerecognition isasortofbiometricidentificationinwhichfacialfeatures areextractedfromaperson'sfaceandsavedasauniqueface print.Biometricfacialrecognitiontechnologyhascaptured the interest of many academics due to its wide range of applications. Face recognition technology is better than other biometric-based recognition techniques like finger, palm,and iris prints becauseofits non-contactoperation. Facerecognitionalgorithmscanalsoidentifysomeonefrom a distancewithoutmaking eyecontactorconversing with the individual. Face recognition software is currently employedatcrimesceneinvestigations,socialmediasites likeFacebook,trainstations,andairports.Facerecognition software can be used to recognize individuals, and the capturedimagecanbeusedincrimereportsandrecordedin a database. Facebook uses face recognition technology to automaticallytagpeopleinimages.Inordertoidentifyaface inanycircumstance,includingwhenlighting,weneedahuge datasetandintricatefeaturestoanalysesfactorslikeageand attitude.Recentresearchshowadvancesinfacialrecognition technologies. Over the past ten years, there has been a substantialprogressinrecognitionmethods.However,atthe moment, the majority of facial recognition algorithms can only function successfully when there are relatively few individuals in a frame, regulated lighting, and adequate conditions for the placement of faces in big data sets, and complexfeaturesarerequiredforfaceidentificationinorder

to be able to manipulate several barriers like lighting, position,andageinginordertouniquelyidentifythevarious participants.Recentyearshaveseenmajorbreakthroughsin facialrecognitiontechnologies.Facerecognitiontechnology hascomealongwayinthepasttenyears.Evenwhenthere aren'tmanyindividualsintheframe,themajorityoffacial recognitionalgorithmsnowinuseperformeffectively.These methodshavealsobeenputtothetestusingacceptableface positioning, controlled lighting, and clear photos. Without regard to illumination or facial location, the facial recognitionsystemproposedinthisstudyforanattendance system can recognize many faces in a frame. The abrupt coronavirus outbreak caused many adjustments in everyone'slives.Forseveraldays,themajorityoftheoffices andinstitutionswereclosed.Themostpopularattendance method in many universities and colleges is based on the biometric system. Nevertheless, the biometric attendance system disseminates the virus. So Biometric attendance system is replaced by Face Recognition Based Attendance systemtoMaintainthesafetyofthestudentsandfaculty.

I. LITERATURE REVIEW MATERIALS AND METHODOLOGY

2.1. Literature Review

Theauthorspresentedamodelforanautomaticattendance system. One of the most important aspects of Although creating a computer system that is similar to human perceptionisstillanactiveareaofresearch,humansuseour abilityto perceive well on a dailybasis.The earliestfacial recognitionstudydatesbacktothe1950sinpsychologyand the1960sinengineering(BrunerandTagiuri1954).Someof theearliestresearchinthisareamaybefoundinDarwin's (1972)studyonemotionalfacialexpression(alsoseeEkman (1998)) and Galton's (1888) study on facial profile-based biometrics.However,afterKanade'sseminalwork[1973], researchonautomaticfacialrecognitionstartedinthe1970s [Kelly1970].In-depthresearchonavarietyofaspectsofface recognitionbyhumansandrobotshasbeenconductedover thepast30yearsbypsychophysicists,neuroscientists,and engineers.

Inthepast15years,researchhasbeenconcentratedonhow tofullymodularizefacerecognitionsystemsbyaddressing issueslikethelocalizationofafaceinagivenimageorvideo clipandtheextractionofcharacteristicsliketheeyes,lips,

and so forth. In the meanwhile, significant advancements have been made in the classification model design for efficient facial recognition software. In tests using sizable databases, the efficacy of Eigenfaces (Kirby and Sirovich 1990;TurkandPentland1991)andFisher-faces(Belhumeur etal.1997;EtemadandChellappa1997;Zhaoetal.1998)has been shown. It has been quite effective to accommodate users appropriately when using feature-based graph matching[Wiskottetal.1997].

a. Materials

1. Node MCU:

SpecificallycreatedforInternetofThings(IoT)applications, NodeMCUisadeveloperboardwithopen-sourceLua-based firmware.ItfeatureshardwarebasedontheESP-12module and firmware that runs on the ESP8266 Wi-Fi SoC from Espressif Systems. Specifications and Features of the NodeMCUESP32PinoutDevelopmentBoard.TheNodeMCU ESP32boardisactivelysupportedbyESPHome(alsoknown as ESP32-DevkitC in some cases). Prefer ESP32 and nodemcu-32sastheboardtypewhentheESPHomewizard asksforyourplatform.BecausetheESP32boardscommonly usetheinternalGPIOpinnumberingoftheboard,thereisno need to bother about additional pins having predefined names.TheESP32CameraModulewasmadebyAI-Thinker A Wi-Fi + Bluetooth/BLE chip and a 32-bit CPU form the foundationofthecontroller.Bothanexternal4MPSRAMand aninternal520KBSRAMarepresent.TheUART,SPI,I2C, PWM, ADC, and DAC are supported by its GPIO Pins. The module is combined with the The maximum camera resolution, up to 1600 1200, is provided by the OV2640 CameraModule.The24-pingold-platedconnectorusedto connect the camera to the ESP32 CAM Board is used. SD cardsupto4GBincapacitycanbeinsertedintotheboard. ImagestakenaresavedtotheSDCard.

signal that microcontrollers can understand is made incrediblysimplebyanFTDIchip.Thereisnoprogrammer chiponthePCB.Therefore,thisboardmaybeprogrammed usinganyUSB-to-TTLModule.FTDIModulesbasedonthe CP2102 or CP2104 chip, or any other chip, are widely accessible.

2. Future Technology Devices International:

A popular IC for USB-to-TTL converters is the FTDI chip. They are utilized to USB-connect gadgets like Arduino to laptops.Inotherwords,convertingaUSBsignaltoaUART

3.

Theconductiveconnectionsbetweentheelementsincontact inanyelectricalcircuitryaremadeviawires.Theyshould have no resistance and offer flawless connectivity. They appear as attractive coloured jumper wires on the breadboard.

4. Arduino IDE compiler:

Arduino is an open-source electronics platform built primarilyonuser-friendlyhardwareandsoftwaretools.Our software is uploaded into the microcontroller using AVRdudeandanAVR-GCCcompilerusingtheArduinoIDE.OpensourcesoftwarecalledtheArduinoIDEisusedtocreateand upload code to Arduino boards. For different operating systems,includingWindows,MacOSX,andLinux,theIDE programmedisappropriate.TheprogramminglanguagesC and C++ are supported. Integrated Development Environmentisreferredtointhissentence.

2.3. Methodology

Using face recognition as a consideration, we gathered journal papers that matched the attendance system keywords. Journals, studies, and papers from the last five years, namely 2015, are what we gather. We encourage English-languagepapersacrossalltheperiodicalswegather. Connect the 5V and GND pins of the ESP32 to the 5V and GNDpinsoftheFTDImodule.ConnectRxtoUOTandTxto UORPininasamemanner.TheIO0andGNDpinsmustbe communicated, most importantly. The system will enter programmingmodeasaresult.Oncethecodingisdone,you can disconnect it. In this scenario, researchers will not employ the ESP webserver example as a whole, but an alternative streaming technique. We have to add another ESPCAMlibraryasaresult.TheESP32CAMlibraryprovides anobject-orientedAPIforinteracting.Itisafrontendforthe esp32-camera library. The code needs a small adjustment before being uploaded. Your Wi-Fi network's SSID and passwordshouldbechanged.Itshouldnowbecompiledand uploaded to the ESP32 CAM Board. But each time you upload, you need to take a few specific actions. To ensure that the IO0 pin is shorted to ground when you push the uploadbutton,checkit.Ifyounoticedotsanddashesduring uploading,presstheresetbuttonrightaway.Afterthecode hasbeenuploaded,resetthebutton,andthendisconnectthe I01pinfromGround.Presstheresetbuttononceagainifthe Serial Monitor's output is still not present. In order to capturetheattendancefromtheURL,copytheaccessibleIP address.Theuserswhoneedtobedetectedshouldnowbe added.We'refinallypreparedtogo.Runthecodethenhave thesubjectfacetheESP32camerawhilestandinginfrontof it.

III. MODELING AND ANALYSIS

IV.RESULTS, DISCUSSION, AND CONCLUSION

The "Facial Recognition Based Attendance System" projecthasbeensuccessfullyimplementedandtested.Itwas createdbymergingfeaturesfromallofthehardwareused. Everymodule'sexistencehasbeencarefullyconsideredand arranged,whichhelpstheunitfunctionatitsbest.Eachface that is recognized and matched with an enrolled face has attendancerecordedintherespectivedatabase.Inaddition to having a quicker response time, this approach will be moreeffectiveatdistinguishingseveralfacesfromasingle frame. Users can communicate with the system using a graphical user interface (GUI). The three main choices available to users are student registration, teacher registration, and attendance marking. Students must thoroughlyfilloutthestudentregistrationform.Whenyou press the register button, the camera instantly turns on, opens a window, and starts looking for faces in the background.Afterthat,until7sampleshavebeengathered or CRTL+Q has been depressed, the camera will start shootingpicturesautomatically.Followingpre-processing, these photographs are saved in the training images directory.Inthedatabaseareincludedtheperson'sname, attendancedate,andtime.Thestrategydescribedabovewill producethebestresults.Thisisaccomplishedbycombining OpenCVforframeextractionwithdlibforfacialrecognition. This approach will be more precise in Then, based on psychologicalresearchandthelessonswe'velearnedfrom creating algorithms, we provide research hypotheses concerning face recognition. We hypothesize that many processes are involved in human identification of both familiarandunknownfaces.

VI. REFERENCES

1. BEYMER, D.J.AND POGGIO, T. 1995. Face recognition from one example view. In Proceedings, InternationalConferenceonComputerVision.500–507.

2.Hapani,Smit,etal."AutomatedAttendanceSystemUsing ImageProcessing."2018FourthInternationalConferenceon Computing Communication Control and Automation (ICCUBEA).IEEE,2018.

3. Lukas, Samuel, et al. "Student attendance system in classroom using face recognition technique." 2016 International Conference on Information and CommunicationTechnologyConvergence(ICTC).IEEE,2016.

4.Ahmedi,A.,Nandyal,S.:Anautomaticattendancesystem using image processing. Int. J. Eng. Sci. (IJES) 4(11), 1–8 (2015).

5. Attendance System based on Face Recognition Venkata KalyanPolamarasetty,MuralidharReddyReddem,Dheeraj Ravi,MahithSaiMadala.

6.FaceRecognitionBasedAttendanceSystemNandhiniR, DuraimuruganN.

7. An Attendance Marking Systembased on Face Recognition" writtenbyKhemPuthea,RudyHartantoand RisanuriHidayat.

8. Class Attendance Management System Using Face Recognition, Omar Abdul Rhman Salim Department of ElectricalandComputerEngineering,FacultyofEngineering International Islamic University Malaysia, Kuala Lumpur, Malaysiao.salem92@gmail.com.

9.Salim,OmarAbdulRahman,RashidahFunkeOlanrewaju, andWasiuAdebayoBalogun."Classattendancemanagement system using face recognition." 2018 7th International ConferenceonComputerandCommunicationEngineering (ICCCE).IEEE,2018.

10.https://www.researchgate.net/publication/326261079_ Face_detection_system_for_attendance_of_class_students