Cardless Atm Transactions With Security System Using Visible Light Communication

Cardless Atm Transactions With Security System Using Visible Light Communication | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cardless Atm Transactions With Security System Using Visible Light Communication S V Vinodhini, Tamizh Kumaran L, Thaarun Kumar JK, R A Thayananthan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6664979/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The physical card is replaced with a LiFi module with a real-time integrated finger-vein recognition system for automated teller machine authentication. The technology, which is based on an integrated LiFi platform, includes a sophisticated algorithm for detecting finger veins. There are three hardware components in the suggested system: an image-capturing module, an embedded main board, and a human-machine communication module. According to the system's structural design, finger-vein images are captured using the image acquisition module. On the embedded main board, which also includes a communication port and a microcontroller chip, the finger-vein identification mechanism is implemented. Results of recognition are displayed and user input is taken in by the human-machine communication module. The LiFi module is used to deliver the user's data instead of the card. The vein will be scanned by the ATM. The transaction can be successfully completed if the finger veins match. If the vein doesn't match, it will use GSM technology to deliver the OTP message to the authorized user. Arduino mega controller Lifi MEMS GSM UART FVR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 I. Introduction Users of computer systems nowadays are becoming more interested in various biometric identification solutions. The applications of identifying technology are not limited. Since fingerprint technology provides for a higher level of information protection, both public and commercial entities are interested in it. Information technology companies are interested in fingerprint, face, voice, and iris recognition technologies in order to monitor external access to their network. The cycle of a typical online business's transaction processing has long had the weakest link: payment processing. Despite the development of technology for E-commerce applications, security issues, and serious breaches have been associated with the payment-related activity. Several financial institutions are seeking potential answers to this issue as fraud rates rise year after year. Biometric payment technology has lately drawn increasing interest as a potential means of reducing identity theft among those new technologies for handling payment processing [1]. The Nigerian central bank (Central Bank of Nigeria) plans to implement biometric verification of point-of-sale (POS) and automated teller machine(ATM) by 2015. [2] in an effort to address concerns about the security of consumers' payments and prevent losses due to PIN breach. After the circular mandating the migration from a Magstripe type of debit card to a chip and Pin (EMV compliant) type of debit card, the apex bank has made a significant step to earn the trust of ATM users. According to statistics, this endeavor has 90% lessened the incidents of fraud because it is nearly impossible for would-be criminals to clone debit cards to commit fraud, as was the case in the pre-migration era, many consumers are now using these electronic channels (ATMs and PoS) to make their purchases. Customers may benefit from Interswitch's e-payment options including Paydirect, Autopay, Direct Debit, Verve Card, Quickteller, Webpay, and Smartgov. The apex bank is considering using biometric authentication for POS and ATMs to address the protection of clients' funds and prevent losses due to PIN breach by 2015. [3] Fingerprint-based authentication may be an alternative to password-based authentication. Fingerprint-based identification is one of the biometric identification strategies that has undergone the greatest development and testing. [4]Fingerprint-based authentication may be a rival to password-based authentication. Fingerprint-based identification is one of the most advanced and tried biometric identification techniques. The ATM terminal uses a high-resolution fingerprint scanner to record a fingerprint image at the time of the transaction. The prevention of customer attacks may depend critically on bank security procedures. Security is becoming a top priority in all kinds of activity. Nowadays, criminal behaviour is prevalent everywhere. Thus, the government and business sectors place a high priority on security requirements with every creation. This will allow for worldwide privacy. As a result, this project was developed with the goal of providing privacy through security level. The picture capturing module, embedded main board, and human machine communication module are the three crucial parts of this FVR system. Every element is essential to the project's success. In this study, there have been two key areas of focus. Identification and authentication are two such procedures. Using finger vein recognition, the FVR system conducts the authentication procedure. Every time the user uses the device, a scan of their finger vein is conducted and a comparison is made. picture scanning, palm print scanning, print security, and certain recognition methods. Vein scanning is used by the FVR system. It is exceedingly challenging to update a user's vein information because it is biologically based. Hence, this system can offer greater protection than any other degree of security. We are emphasizing maximum security using RFID technology in our FVR system. Each and every user will initially receive a single RFID secret card. The effective first communication between the user and the gadget will result from this. The amount of crimes, including ATM robberies, unlawful personnel entry into major enterprises, unauthorized data entry, etc., is rising daily in our high-tech environment. The flaws in the current security mechanisms are the primary sources of these issues. Due to the large volume of digital information and the great value that is usually placed on it, digital security has taken on a unique significance. Passwords are typically used for security. Applications for user authentication must be effective in order to safeguard information security. Many authentication systems have been created as a result of the rising number of risks to data security. Here, we present a novel ATM network authentication method that uses finger vein recognition technology. A new, cutting-edge method of completing ATM transactions without the requirement for a physical ATM card is through cardless transactions using Visible Light Communication (VLC) technology. Instead, with the usage of their transmitter module, a client can connect to the ATM network utilising VLC technology, which enables the ATM and transmitter to communicate through visible light signals. In summary, the advent of cardless ATM transactions employing Visible Light Communication technology is an encouraging development in the banking sector that provides customers with improved security, convenience, and accessibility. II. Implementation Figure 1 represents the transmitter portion is a power source, embedded unit, and LiFi transmitter. The embedded unit is made up of Arduino Atmega328. The power supply gives power to the Arduino. The Arduino sends the card details to the UART Lifi transmitter. The whole data bytes are sent sequentially, in single bit by UART to the LED. Figure 2 denotes the receiver system consists of a photovoltaic cell that receives the data from LED. The UART receiver sends these data to the microcontroller (Arduino Atmega). The controller compares the data received with that of the test data. If both data match relay indicates that the transaction is successful. If both the datas did not match then an SMS is sent to the cardholder. Typically MEMS is used here for security purposes. If someone tries to break open the ATM theft alert is sent to the concerned authority. Figure 3 is the flowchart. The cardholder's finger picture is read from the biometric (here the Arduino sends these images on button click for testing purposes). It is then checked against the test picture after being preprocessed, deconstructed, and extracted. The test picture is acquired from the database; in this case, it is obtained through the MATLAB program for simplicity. The test picture is deconstructed, extracted, and preprocessed. Afterward, we compare this image to the one the customer provided. In the event that both are correct, the transaction is approved; otherwise, it is not. Transmitter section is represented in Fig. 4 . The finger-vein biometric pattern for personal identification shows promise in terms of ease of use and security. Due to the vein's internal location and near-complete obscurity to the human sight, it is challenging to imitate or steal. The finger-vein pattern can only be obtained from a living organism. The fact that the patient's finger vein was successfully obtained is still alive is therefore an evidence and natural sign. The account holder's credit card information is sent via a LiFi transmitter. The compares the information it gets with the information derived from the finger vein scanner. If both sets of data are compatible, the transaction is continued. If an unidentified user uses a WiFi card, the account holder will get an OTP for verification. A 5v power supply, embedded unit, and finally a Lifi source, such as an LED, make up the transmitter part. A simple Arduino ATMEGA-328 microcontroller serves as the embedded device. The UART port of the Arduino is used to connect the LIFI module to it. Data is sent and received by the LIFI module through the UART port. The microcontroller first reads the card information before converting it to a format that computers can understand. It is then transmitted to UART (Universal Asynchronous Receiver Transmitter ). It transmits Arduino's bit data to the LED. The led will emit light if the data from the UART is 1, and no light will be generated if the data is 0. Here, the switch has no use other than to provide the information for the account holder's various cards. The receiver portion is shown in Fig. 5 . It is made up of a photovoltaic cell that receives the LED's data. Shift registers, which are part of UARTs, are used to transform serial data to parallel data or vice versa. The Arduino Atmega 328 is then provided the data. The receiver sends one data to the Arduino, and MATLAB provides the second data—the data to be referenced—to the Arduino. This information will be gathered instantly from the vein scanner or ATM-based biometric. The data from the two veins are then compared. The relay module enables the transaction to be handled further if both sets of data match. If not, the account holder receives an OTP. The account holder has the option to enter the OTP transaction. A GSM module for sending OTP is also included in the receiver. The system also includes an ATM-integrated MEMS system. It can notify the appropriate government in the event of any theft. III. Simulation and Result Modules : Image Acquisition Preprocessing Segmentation Feature Extraction Classification MODULE DESCRIPTION : 1. Image Acquisition : Images are acquired from Gallery. 2.Preprocessing : The objective of the preprocessing stage is to use potential image-enhancing methods on the image to obtain the required visual quality. methods for enhancing photographs: Grayscale Image Down sampling ROI region extraction i. Grayscale Image : The image is of the RGB (red, green, and blue) kind, which is an additive color. For additional processing, the picture is converted into a grayscale version. ii. Down sampling : The finger vein picture was shrunk by a factor of 0.5 during downsampling. iii. ROI Region Extraction : At that point, a binary mask was generated to extract just the finger vein region. 3. Segmentation : The segmentation of the finger vein is carried out following the preprocessing step. The segmentation of finger veins using the repeated line tracking approach. Following that, the segmented result for binaries is thresholded, and noise is removed from the segmented result using a median filter. 4. Feature Extraction : Feature extraction is carried out following segmentation. Using a local binary pattern is how it is done. 5. Classification : The retrieved characteristics are used in the classification procedure. The adoption of k's nearest neighbour is the primary novelty in this (KNN). The retrieved characteristics are applied to the KNN classifier, and classification is completed. It has been demonstrated that positive outcomes are possible. IV. Conclusion Biometrics is the term for the process of automatically identifying someone based on their physical, behavioral, and/or physiological characteristics. Increasing overall security is the main objective of using biometric solutions. Biometrics offer improved levels of security and convenience compared to traditional methods of personal recognition. In some circumstances, biometrics might be able to replace or outperform existing technologies. In certain cases, it's the only practical strategy. The level of security ensured by the deployment of biometric technologies and the discrepancy that may exist between the perceived and actual sense of security offered must be understood by decision-makers. The efficiency of the biometric system will be determined equally by the other components of the total identification or authentication process, which includes the biometric system. With all types of applications, security is becoming increasingly important. This project is being carried out in a way that raises the bar for security. Because to its ease of use and security, the finger vein is a potential biometric pattern for personal identification. The vein is difficult to manufacture or steal since it is concealed within the body and typically cannot be seen by humans. Non-invasive, contactless finger vein collection ensures user comfort and hygiene, making it more acceptable. Thus, there is greater optimism that this method will raise the bar for security. Another significant point to consider is the utilization of visible light for data transport and communication. Visible light is used to speed up data transfer and enhance security. Declarations Data Availability: Yes, Data sharing is not applicable to this article as no datasets were generated or analysed during the current study. Ethics statement: Not Applicable Consent to Publish: Not Applicable Consent to Participate: Not Applicable Funding details: This work is not provided with any financial support. Conflict of interest There is no conflict of interest. References K. Jain, S. Pankanti, S. Prabhakar, H. Lin, and A. Ross, “Biometrics:a grand challenge”, Proceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 2, pp. 935-942, 2004. P. Corcoran and A. Cucos, “Techniques for securing multimedia content inconsumer electronic appliances using biometric signatures,” IEEE Transactions on Consumer Electronics, vol 51, no. 2, pp. 545-551, May 2005 P. J. Phillips, A. Martin C. L. Wilson and M. Przybocki, “An Introduction to Evaluating Biometric Systems,” IEEE Computer, Vol.33, No.2, Feb. 2000, pp. 56-63. S. Pankanti, R. M. Bolle and A. Jain, “Biometrics: The Future of Identification,” IEEE Computer, Vol.33, No.2, Feb. 2000, pp. 46-49. H. Lee, S. Lee, T. Kim, and HyokyungBahn, “Secure user identification for consumer electronics devices,” IEEE Transactions on Consumer Electronics, vol.54, no.4, pp.1798-1802, Nov. 2008. Wang , J. Li, and G. Memik, “User identification based on finger vein patterns for consumer electronics devices”, IEEE Transactions on Consumer Electronics, vol. 56, no. 2, pp. 799-804, 2010. Mulyono and S. J. Horng, “A study of finger vein biometric for personal identification”, Proceedings of the International Symposium Biometrics and Security Technologies, pp. 134-141, 2008. Y. G. Dai and B. N. Huang, “A method for capturing the finger-veinimage using non uniform intensity infrared light”, Image and Signal Processing, vol.4, pp.27-30, 2008 Sun, C. Lin, M. Li, H. Lin, and Q. Chen, “A DSP-based finger vein authentication system”, Proceedings of the Fourth International Conference on Intelligent Computation Technology and Automation,pp.333-336, 2011. D. Hwang and I. Verbauwhede, “Design of portable biometric authenticators - energy, performance, and security tradeoffs,” IEEETransactions on Consumer Electronics, vol. 50, no. 4, pp. 1222-1231,Nov.2004. Miura, A. Nagasaka, and T. Miyatake, “Feature extraction of finger vein patterns based on repeated line tracking and its application to personal identification”, Machine Vision Application, vol. 15, no.4,pp.194–203, 2004. W. Song, T. Kim, H. C. Kim, J. H. Choi, H. Kong and S. Lee, “A finger-vein verification system using mean curvature”, Pattern Recognition Letters, vol. 32, no.11, pp. 1541-1547, 2011. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6664979","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":466954952,"identity":"ec448942-64d8-44f5-8f32-fcaed8e4fcc0","order_by":0,"name":"S V 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Introduction","content":"\u003cp\u003eUsers of computer systems nowadays are becoming more interested in various biometric identification solutions. The applications of identifying technology are not limited. Since fingerprint technology provides for a higher level of information protection, both public and commercial entities are interested in it. Information technology companies are interested in fingerprint, face, voice, and iris recognition technologies in order to monitor external access to their network. The cycle of a typical online business's transaction processing has long had the weakest link: payment processing.\u003c/p\u003e \u003cp\u003eDespite the development of technology for E-commerce applications, security issues, and serious breaches have been associated with the payment-related activity. Several financial institutions are seeking potential answers to this issue as fraud rates rise year after year. Biometric payment technology has lately drawn increasing interest as a potential means of reducing identity theft among those new technologies for handling payment processing [1]. The Nigerian central bank (Central Bank of Nigeria) plans to implement biometric verification of point-of-sale (POS) and automated teller machine(ATM) by 2015. [2] in an effort to address concerns about the security of consumers' payments and prevent losses due to PIN breach.\u003c/p\u003e \u003cp\u003eAfter the circular mandating the migration from a Magstripe type of debit card to a chip and Pin (EMV compliant) type of debit card, the apex bank has made a significant step to earn the trust of ATM users. According to statistics, this endeavor has 90% lessened the incidents of fraud because it is nearly impossible for would-be criminals to clone debit cards to commit fraud, as was the case in the pre-migration era, many consumers are now using these electronic channels (ATMs and PoS) to make their purchases. Customers may benefit from Interswitch's e-payment options including Paydirect, Autopay, Direct Debit, Verve Card, Quickteller, Webpay, and Smartgov. The apex bank is considering using biometric authentication for POS and ATMs to address the protection of clients' funds and prevent losses due to PIN breach by 2015. [3] Fingerprint-based authentication may be an alternative to password-based authentication. Fingerprint-based identification is one of the biometric identification strategies that has undergone the greatest development and testing.\u003c/p\u003e \u003cp\u003e[4]Fingerprint-based authentication may be a rival to password-based authentication. Fingerprint-based identification is one of the most advanced and tried biometric identification techniques.\u003c/p\u003e \u003cp\u003eThe ATM terminal uses a high-resolution fingerprint scanner to record a fingerprint image at the time of the transaction. The prevention of customer attacks may depend critically on bank security procedures. Security is becoming a top priority in all kinds of activity. Nowadays, criminal behaviour is prevalent everywhere. Thus, the government and business sectors place a high priority on security requirements with every creation. This will allow for worldwide privacy. As a result, this project was developed with the goal of providing privacy through security level. The picture capturing module, embedded main board, and human machine communication module are the three crucial parts of this FVR system. Every element is essential to the project's success. In this study, there have been two key areas of focus. Identification and authentication are two such procedures. Using finger vein recognition, the FVR system conducts the authentication procedure. Every time the user uses the device, a scan of their finger vein is conducted and a comparison is made. picture scanning, palm print scanning, print security, and certain recognition methods. Vein scanning is used by the FVR system. It is exceedingly challenging to update a user's vein information because it is biologically based. Hence, this system can offer greater protection than any other degree of security. We are emphasizing maximum security using RFID technology in our FVR system. Each and every user will initially receive a single RFID secret card. The effective first communication between the user and the gadget will result from this. The amount of crimes, including ATM robberies, unlawful personnel entry into major enterprises, unauthorized data entry, etc., is rising daily in our high-tech environment. The flaws in the current security mechanisms are the primary sources of these issues. Due to the large volume of digital information and the great value that is usually placed on it, digital security has taken on a unique significance. Passwords are typically used for security. Applications for user authentication must be effective in order to safeguard information security. Many authentication systems have been created as a result of the rising number of risks to data security. Here, we present a novel ATM network authentication method that uses finger vein recognition technology. A new, cutting-edge method of completing ATM transactions without the requirement for a physical ATM card is through cardless transactions using Visible Light Communication (VLC) technology. Instead, with the usage of their transmitter module, a client can connect to the ATM network utilising VLC technology, which enables the ATM and transmitter to communicate through visible light signals. In summary, the advent of cardless ATM transactions employing Visible Light Communication technology is an encouraging development in the banking sector that provides customers with improved security, convenience, and accessibility.\u003c/p\u003e"},{"header":"II. Implementation","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e represents the transmitter portion is a power source, embedded unit, and LiFi transmitter. The embedded unit is made up of Arduino Atmega328. The power supply gives power to the Arduino. The Arduino sends the card details to the UART Lifi transmitter. The whole data bytes are sent sequentially, in single bit by UART to the LED.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e denotes the receiver system consists of a photovoltaic cell that receives the data from LED. The UART receiver sends these data to the microcontroller (Arduino Atmega). The controller compares the data received with that of the test data. If both data match relay indicates that the transaction is successful. If both the datas did not match then an SMS is sent to the cardholder. Typically MEMS is used here for security purposes. If someone tries to break open the ATM theft alert is sent to the concerned authority.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e is the flowchart. The cardholder's finger picture is read from the biometric (here the Arduino sends these images on button click for testing purposes). It is then checked against the test picture after being preprocessed, deconstructed, and extracted. The test picture is acquired from the database; in this case, it is obtained through the MATLAB program for simplicity. The test picture is deconstructed, extracted, and preprocessed. Afterward, we compare this image to the one the customer provided. In the event that both are correct, the transaction is approved; otherwise, it is not.\u003c/p\u003e \u003cp\u003eTransmitter section is represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The finger-vein biometric pattern for personal identification shows promise in terms of ease of use and security. Due to the vein's internal location and near-complete obscurity to the human sight, it is challenging to imitate or steal. The finger-vein pattern can only be obtained from a living organism. The fact that the patient's finger vein was successfully obtained is still alive is therefore an evidence and natural sign. The account holder's credit card information is sent via a LiFi transmitter. The compares the information it gets with the information derived from the finger vein scanner. If both sets of data are compatible, the transaction is continued. If an unidentified user uses a WiFi card, the account holder will get an OTP for verification. A 5v power supply, embedded unit, and finally a Lifi source, such as an LED, make up the transmitter part. A simple Arduino ATMEGA-328 microcontroller serves as the embedded device. The UART port of the Arduino is used to connect the LIFI module to it. Data is sent and received by the LIFI module through the UART port. The microcontroller first reads the card information before converting it to a format that computers can understand. It is then transmitted to UART (Universal Asynchronous Receiver Transmitter ). It transmits Arduino's bit data to the LED. The led will emit light if the data from the UART is 1, and no light will be generated if the data is 0. Here, the switch has no use other than to provide the information for the account holder's various cards.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe receiver portion is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. It is made up of a photovoltaic cell that receives the LED's data. Shift registers, which are part of UARTs, are used to transform serial data to parallel data or vice versa. The Arduino Atmega 328 is then provided the data. The receiver sends one data to the Arduino, and MATLAB provides the second data\u0026mdash;the data to be referenced\u0026mdash;to the Arduino. This information will be gathered instantly from the vein scanner or ATM-based biometric. The data from the two veins are then compared. The relay module enables the transaction to be handled further if both sets of data match. If not, the account holder receives an OTP. The account holder has the option to enter the OTP transaction. A GSM module for sending OTP is also included in the receiver. The system also includes an ATM-integrated MEMS system. It can notify the appropriate government in the event of any theft.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"III. Simulation and Result","content":"\u003cp\u003e \u003cb\u003eModules\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eImage Acquisition\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePreprocessing\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSegmentation\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFeature Extraction\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eMODULE DESCRIPTION\u003c/span\u003e:\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e1. Image Acquisition\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eImages are acquired from Gallery.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e2.Preprocessing\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eThe objective of the preprocessing stage is to use potential image-enhancing methods on the image to obtain the required visual quality. methods for enhancing photographs:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGrayscale Image\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDown sampling\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eROI region extraction\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ei. Grayscale Image\u003c/b\u003e: The image is of the RGB (red, green, and blue) kind, which is an additive color. For additional processing, the picture is converted into a grayscale version.\u003c/p\u003e \u003cp\u003e \u003cb\u003eii. Down sampling\u003c/b\u003e: The finger vein picture was shrunk by a factor of 0.5 during downsampling.\u003c/p\u003e \u003cp\u003e \u003cb\u003eiii. ROI Region Extraction\u003c/b\u003e: At that point, a binary mask was generated to extract just the finger vein region.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e3. Segmentation\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eThe segmentation of the finger vein is carried out following the preprocessing step. The segmentation of finger veins using the repeated line tracking approach. Following that, the segmented result for binaries is thresholded, and noise is removed from the segmented result using a median filter.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e4. Feature Extraction\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eFeature extraction is carried out following segmentation. Using a local binary pattern is how it is done.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e5. Classification\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eThe retrieved characteristics are used in the classification procedure. The adoption of k's nearest neighbour is the primary novelty in this (KNN). The retrieved characteristics are applied to the KNN classifier, and classification is completed. It has been demonstrated that positive outcomes are possible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"IV. Conclusion","content":"\u003cp\u003eBiometrics is the term for the process of automatically identifying someone based on their physical, behavioral, and/or physiological characteristics. Increasing overall security is the main objective of using biometric solutions. Biometrics offer improved levels of security and convenience compared to traditional methods of personal recognition. In some circumstances, biometrics might be able to replace or outperform existing technologies. In certain cases, it's the only practical strategy. The level of security ensured by the deployment of biometric technologies and the discrepancy that may exist between the perceived and actual sense of security offered must be understood by decision-makers. The efficiency of the biometric system will be determined equally by the other components of the total identification or authentication process, which includes the biometric system. With all types of applications, security is becoming increasingly important. This project is being carried out in a way that raises the bar for security. Because to its ease of use and security, the finger vein is a potential biometric pattern for personal identification. The vein is difficult to manufacture or steal since it is concealed within the body and typically cannot be seen by humans. Non-invasive, contactless finger vein collection ensures user comfort and hygiene, making it more acceptable. Thus, there is greater optimism that this method will raise the bar for security. Another significant point to consider is the utilization of visible light for data transport and communication. Visible light is used to speed up data transfer and enhance security.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eYes, Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement:\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding details:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is not provided with any financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eK. Jain, S. Pankanti, S. Prabhakar, H. Lin, and A. Ross, \u0026ldquo;Biometrics:a grand challenge\u0026rdquo;, Proceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 2, pp. 935-942, 2004.\u003c/li\u003e\n \u003cli\u003eP. Corcoran and A. Cucos, \u0026ldquo;Techniques for securing multimedia content inconsumer electronic appliances using biometric signatures,\u0026rdquo; IEEE Transactions on Consumer Electronics, vol 51, no. 2, pp. 545-551, May 2005\u003c/li\u003e\n \u003cli\u003eP. J. Phillips, A. Martin C. L. Wilson and M. Przybocki, \u0026ldquo;An Introduction to Evaluating Biometric Systems,\u0026rdquo; IEEE Computer, Vol.33, No.2, Feb. 2000, pp. 56-63.\u003c/li\u003e\n \u003cli\u003eS. Pankanti, R. M. Bolle and A. Jain, \u0026ldquo;Biometrics: The Future of Identification,\u0026rdquo; IEEE Computer, Vol.33, No.2, Feb. 2000, pp. 46-49.\u003c/li\u003e\n \u003cli\u003eH. Lee, S. Lee, T. Kim, and HyokyungBahn, \u0026ldquo;Secure user identification for consumer electronics devices,\u0026rdquo; IEEE Transactions on Consumer Electronics, vol.54, no.4, pp.1798-1802, Nov. 2008.\u003c/li\u003e\n \u003cli\u003eWang , J. Li, and G. Memik, \u0026ldquo;User identification based on finger vein patterns for consumer electronics devices\u0026rdquo;, IEEE Transactions on Consumer Electronics, vol. 56, no. 2, pp. 799-804, 2010.\u003c/li\u003e\n \u003cli\u003eMulyono and S. J. Horng, \u0026ldquo;A study of finger vein biometric for personal identification\u0026rdquo;, Proceedings of the International Symposium Biometrics and Security Technologies, pp. 134-141, 2008.\u003c/li\u003e\n \u003cli\u003eY. G. Dai and B. N. Huang, \u0026ldquo;A method for capturing the finger-veinimage using non uniform intensity infrared light\u0026rdquo;, Image and Signal Processing, vol.4, pp.27-30, 2008\u003c/li\u003e\n \u003cli\u003eSun, C. Lin, M. Li, H. Lin, and Q. Chen, \u0026ldquo;A DSP-based finger vein authentication system\u0026rdquo;, Proceedings of the Fourth International Conference on Intelligent Computation Technology and Automation,pp.333-336, 2011.\u003c/li\u003e\n \u003cli\u003eD. Hwang and I. Verbauwhede, \u0026ldquo;Design of portable biometric authenticators - energy, performance, and security tradeoffs,\u0026rdquo; IEEETransactions on Consumer Electronics, vol. 50, no. 4, pp. 1222-1231,Nov.2004.\u003c/li\u003e\n \u003cli\u003eMiura, A. Nagasaka, and T. Miyatake, \u0026ldquo;Feature extraction of finger vein patterns based on repeated line tracking and its application to personal identification\u0026rdquo;, Machine Vision Application, vol. 15, no.4,pp.194\u0026ndash;203, 2004.\u003c/li\u003e\n \u003cli\u003eW. Song, T. Kim, H. C. Kim, J. H. Choi, H. Kong and S. Lee, \u0026ldquo;A finger-vein verification system using mean curvature\u0026rdquo;, Pattern Recognition Letters, vol. 32, no.11, pp. 1541-1547, 2011.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Arduino mega controller, Lifi, MEMS, GSM, UART, FVR","lastPublishedDoi":"10.21203/rs.3.rs-6664979/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6664979/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe physical card is replaced with a LiFi module with a real-time integrated finger-vein recognition system for automated teller machine authentication. The technology, which is based on an integrated LiFi platform, includes a sophisticated algorithm for detecting finger veins. There are three hardware components in the suggested system: an image-capturing module, an embedded main board, and a human-machine communication module. According to the system's structural design, finger-vein images are captured using the image acquisition module. On the embedded main board, which also includes a communication port and a microcontroller chip, the finger-vein identification mechanism is implemented. Results of recognition are displayed and user input is taken in by the human-machine communication module. The LiFi module is used to deliver the user's data instead of the card. The vein will be scanned by the ATM. The transaction can be successfully completed if the finger veins match. If the vein doesn't match, it will use GSM technology to deliver the OTP message to the authorized user.\u003c/p\u003e","manuscriptTitle":"Cardless Atm Transactions With Security System Using Visible Light Communication","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-11 08:33:45","doi":"10.21203/rs.3.rs-6664979/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c36468b7-265c-48f5-aa98-0d3c40705ce1","owner":[],"postedDate":"June 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T07:23:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-11 08:33:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6664979","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6664979","identity":"rs-6664979","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}