Home⇛International Journal of Multidisciplinary: Applied Business and Education Research⇛vol. 6 no. 4 (2025)

Automated Vehicle Access Control System Utilizing Computer Vision-Based License Plate Recognition

Joseph J. Juliano | Marc Kiane A. Armada | Angelito N. Cosadio Jr. | Rickron E. Reyes

Discipline: Mechanical Engineering

 

Abstract:

The evaluation of the Automated Vehicle Access Control System utiliz-ing Computer Vision-Based License Plate Recognition demonstrated excellent performance based on ISO/IEC 25010:2011 quality metrics, achieving a Grand Mean of 3.31, categorized as "Excellent." Individual metrics such as Maintainability (3.38), Portability (3.40), and Reliabil-ity (3.35) ranked highest, reflecting the system's robust quality. The system’s functionality and performance were also rated "Highly Ac-cepted" by respondents, with a Grand Mean of 3.47. Readiness evalua-tions indicated the infrastructure and personnel were "Very Ready" to support implementation, with a Grand Mean of 3.47. These findings align with related studies emphasizing the efficiency of image-based entry management systems employing vehicle and facial recognition technologies, which enhance security, automate access control, and re-duce manual workload. Leveraging advanced techniques like CNN and OpenCV, these systems prove effective in organizational settings, providing real-time monitoring, attendance tracking, and vehicle man-agement capabilities. The high accuracy and readiness demonstrated by the system affirm its reliability and effectiveness for deployment.



References:

  1. Agarwal,  S.  (2023).  YOLOv8  versus  YOLOv7: A study   in   drone   detection. International Journal of Robotics and  Autonomous  Sys-tems.
  2. Agnihotri, A., Saraf, P., & Bapnad, K.R. (2019). A Convolutional  Neural  Network  Approach Towards Self-Driving Cars.
  3. Ajit,  K.,  Gupta,  S.,  &  Singh,  P.  (2020). Efficiency and  accuracy  of  convolutional  neural  net-works in object detection and image recog-nition. International  Journal  of  Computer Vision and Pattern Recognition.
  4. Amjoud, M., & Smith, J. (2020). The role of con-volutional neural networks in object detec-tion.Journal  of  Advanced  Research  in  Ar-tificial Intelligence and Robotics.
  5. Amon,  M.  C.  E.,  Brillantes,  A.  K.  M.,  Billones,  C., Billones,  R.,  Jose,  J.  A.  C.,  Sybingco,  E., Dadios, E., Fillone, A. M., Lim, L. G., & Ban-dala,  A.  (2019). Philippine  license  plate character  recognition  using  Faster  R-CNN with  InceptionV2.Proceedings  of  the  In-ternational    Conference    on    Humanoid, Nanotechnology, Information Technology, Communication    and    Control,    Environ-ment and Management.
  6. Baballe, M., & Dahiru, M. (2023). Advantages of automated  license  plate  recognition  tech-nology.
  7. Bambharolia, S., Patel,  A.,  & Sharma, R. (2017). The  power  of  convolutional  neural  net-works in classification and prediction tasks.Journal of Machine Learning Applications.
  8. Benslimane,  Y.,  Yang,  Z.,  &  Liu,  E.  (2021). Im-proving  information  system  development and maintainability factors through stand-ardized   processes:   An   empirical   study.2021  IEEE  International  Conference  on Industrial  Engineering  and  Engineering Management.
  9. Borbon, J., Javier, J., Llamado, J., Dadios, E. D., & Billones, R. (2021). Coral health identifica-tion  using  image  classification  and  convo-lutional  neural  networks.Proceedings  of the  International  Conference  on  Human-oid,  Nanotechnology,  Information  Tech-nology, Communication and Control, Envi-ronment and Management.
  10. Brillantes,  A.  K.  M.,  Billones,  C.,  Amon,  M.  C.  E., Cero, C., Jose, J. A. C., Billones, R., & Dadios, E. (2019). Philippine license plate detection and  classification  using  Faster  R-CNN  and Feature  Pyramid  Network.Proceedings  of the  International  Conference  on  Human-oid,  Nanotechnology,  Information  Tech-nology, Communication and Control, Envi-ronment and Management.
  11. Brilli, G., Burgio, P., Bertogna, M. (2018) Convo-lutional Neural Networks on Embedded Au-tomotive Platforms: A Qualitative Compar-ison. IEEE   International   Conference   on High  Performance  Computing  &  Simula-tion (HPCS)
  12. Calitz,  C.  (2020). Efficiency  and  accuracy  of ALPR  systems:  Recognition  accuracy  and real-time access control success rate.Jour-nal of Applied Computer Science.
  13. Cao, W., Wang, X., Ming, Z., & Gao, J. (2018) A re-view   on   neural   networks   with   random weightsJuliano et al., 2025 /Automated Vehicle Access Control System Utilizing Computer Vision-Based License Plate RecognitionIJMABER 1975Volume 6 | Number 4| April| 2025
  14. Chaturvedi, A., & Sethi, N. (2013). Automatic Li-cense Plate Recognition System using SURF Features and RBF Neural Network.
  15. Cho, N.,El Asmar, M., Gibson, G. E., &Aramali, V. (2020). Earned Value Management System (EVMS)  Reliability:  A  Review  of  Existing EVMS Literature.
  16. Choi,  H.,  &  Jeong,  J.  (2023). Realtime  Detection of  Table  Objects  and  Text  Areas  for  OCR Preprocessing.
  17. Chu,  Y.,  Yuan,  Z.,  &  Liu,  P.  (2023). Privacy  con-cern and acceptability of driver monitoring system.Emerging  Technologies  and  Fu-ture of Work.
  18. Dao,  H.  (2023).  YOLOv8  in  agriculture:  Surface disease  detection  on  tomatoes.Journal  of Agricultural Technology Research.
  19. Dome,  S.,  &  Sathe,  A.  P.  (2021). Optical  charac-ter  recognition  using  Tesseract  and  classi-fication.Proceedings  of the 2021 Interna-tional   Conference   on   Emerging   Smart Computing and Informatics (ESCI).
  20. Fernandez, S. M. B. (2021). Vehicle management system using RFID.International Journal of Multidisciplinary Research and Analysis.
  21. Flores,  M.  G.  (2020). iWASTE:  An  automated waste  classification  technology  using  su-pervised  learning  with  convolution  neural network and Mf classifier. Journal of Com-puter Science.
  22. Gawali,  N.  V.  (2023). Image  classification  using convolutional   neural   networks.Interna-tional Journal for Research in Applied Sci-ence and Engineering Technology.
  23. Guo,  Y.,  Wang,  L.,  &  Zhang,  Q.  (2017). Perfor-mance of convolutional neural networks in image  classification:  A  study  of  learning rate  and  optimization  algorithms.Journal of Machine Learning Research.
  24. He,  Y.  (2020). Research  on  text  detection  and recognition based on OCR recognition tech-nology.Proceedings  of  the  International Conference  on  Information  Systems  and Computer Aided Education.
  25. He, Z. (2020). Deep learning in image classifica-tion:  A  survey  report.Proceedings  of  the 2020 2nd International Conference on In-formation  Technology  and  Computer  Ap-plication (ITCA).
  26. Huang,  Q.,  &  Zhang,  Y.  (2018). CNN  in  convolu-tion:  A  wider  CNN  architecture  for  im-proved  accuracy  in  image   classification.Journal of Artificial Intelligence Research.
  27. Islam,  M.  S. (2023). Applications of ALPR  in car parking,  access  control,  speed  control,  toll collection,  border  security,  and  traffic  vio-lence    detection.Journal    of    Intelligent Transportation Systems.
  28. Indira,   K.,   Mohan,   K.,   &   Nikhilashwary,   T. (2019). Automatic  license  plate  recogni-tion.Journal  of  Intelligent  Transportation Systems.
  29. Ingale, H., Ingale, B., Ingle, A., Indulkar, P., & In-gale,  H.  (2022). Parking  Management  Sys-tem. International  Journal  of  Creative  Re-search Thoughts (IJCRT).
  30. Iskandar, R., & Kesuma, M. (2022). Designing a real-time-based  optical  character  recogni-tion to detect ID cards.International Jour-nal  of  Electronics  and  Communications Systems.
  31. Jabez, A. A., Hariharasudhan, E., Karthikeyan, J., &  Gowthami,  N.  (2021). Object  detection using  optical  character  recognition  for  ve-hicle management.JETIR.
  32. Jagadamaba,  G.,  Purohit,  S.,  &  Chayashree,  G. (2019). Campus Vehicle Monitoring Through Image Processing.
  33. Joseph,  S.  I.  T.  (2022). Advanced  digital  image processing technique based optical charac-ter recognition of scanned document.Jour-nal of Innovative Image Processing.
  34. Kalyan,   S.   S.,   Pratyusha,   V.,   Nishitha,   N.,   & Ramesh, T. K. (2020). Vehicle detection us-ing  image  processing.2020  IEEE  Interna-tional  Conference  for  Innovation  in  Tech-nology (INOCON).
  35. Kanagarathinam,  K.,  Ravindrakumar,  K.,  Fran-cis,  R.,  &  Ilankannan,  S.  (2019). Steps  In-volved  in  Text  Recognition  and  Recent  Re-search in OCR; A Study
  36. Kang,  J.,  Yu,  R.,  Huang,  X.,  Wu,  M.,  Maharjan,  S., Xie,  S.,  &  Zhang,  Y.  (2019). Blockchain  for Secure and Efficient Data Sharing in Vehic-ular Edge Computing and Networks.
  37. Kavitha, H., Raj, M., Kumar, S. M., Shankar, S., & Dayananda, P. (2023). An automated office and  vehicle  management  system.2023  In
  38. Juliano et al., 2025 /Automated Vehicle Access Control System Utilizing Computer Vision-Based License Plate RecognitionIJMABER1976Volume 6 | Number 4| April|2025ternational  Conference  on  Network,  Mul-timedia    and    Information    Technology (NMITCON).
  39. Kato, G. A., Yamongan, J. S., Manao, J. M., Arcega, R. A., Espino, R. L., Capili, R. D., & Magsum-bol,  J.  V.  (2022). Emerging  technologies  in the Philippines: Internet of Things (IoT).In-ternational Conference Organization.
  40. Kalpana,  E.  (2021). Automated  facial  recogni-tion  entry  management  system  using  im-age processing technique.
  41. Kaur,  G.,  Jaiswal,  A.  K.,  Kumar,  R.,  &  Thakur,  K. (2023).Automatic  license  plate  recogni-tion  system. Proceedings  of  the  Interna-tional  Conference  on  Computing  Commu-nication and Networking Technologies.
  42. Konyuncu,  H.  (2021). A  Comparative  Study  of Handwritten  Character  Recognition  by  us-ing  Image  Processing  and  Neural  Network Techniques
  43. Lou, Z. (2023). DC-YOLOv8: Small-size object de-tection algorithm based on camera sensors.Journal  of  Computer  Vision  and  Pattern Recognition.
  44. Lou, Z. (2023). Improving YOLOv8 for small-size object  detection.Journal  of  Computer  Vi-sion and Pattern Recognition.
  45. Ma,  J.  (2023). Enhancements  to  the  YOLOv8 model   for   remote   sensing   applications.Journal of Remote Sensing Technology.
  46. Mamun,  M.,  &  Deb,  K.  (2019). An  approach  for recognizing  vehicle  based  on  appearance.2019  International  Conference  on  Com-puter,  Communication,  Chemical,  Materi-als and Electronic Engineering (IC4ME2).
  47. Marzuki,  P.,  Syafeeza,  A.R.,  Wong,  Y.C.,  Hamid, N.A., Nur Alisa, A., & Ibrahim M.M. (2019). A design of license plate recognition system using convolutional neural network.
  48. Mehta,  J.,  Talati,  S.,  Upadhyay,  S.,  Valiveti,  S.,  & Raval,  G.  (2023). Regenerating  vital  facial keypoints  for  impostor  identification  from disguised images using CNNNwokoma,  F.  O., 
  49. Odii,  J.  N.,  Ayogu,  I.  I.,  &  Og-bonna,  J.  C.  (2021). Camera-based  OCR scene text detection issues: A review.World Journal  of  Advanced  Research  and  Re-views.
  50. Pandey, G., Lamichhane, N., Subedi, U., & K C, K. (2024). CNN  based  system  for  automatic number  plate  recognition.Journal  of  Soft Computing Paradigm.
  51. Panganiban,  E.,  &  Dela  Cruz,  J.  (2017). RFID-based   vehicle   monitoring   system. 2017 IEEE 9th International Conference on Hu-manoid,     Nanotechnology,     Information Technology,  Communication  and  Control, Environment, and Management
  52. Pavithra,  B.,  Suchitra,  S.,  Subbulakshmi,  P.,  & Faustina, J. (2019). RFID based smart auto-matic    vehicle    management    system    for healthcare applications.2019 3rd Interna-tional Conference on Electronics, Commu-nication and Aerospace Technology (ICECA).
  53. Picco,  A.,  Stuiver,  A.,  de  Winter, J.,  &  de Waard, D. (2023). The use of monitoring and feed-back  devices  in  driving:  An  assessment  of acceptability and its key determinants.
  54. Pilania,  U.,  &  Singh,  S.  (2022). Implementation of  image-based  attendance  system.Inter-national  Conference  Electronic  Systems, Signal  Processing  and  Computing  Tech-nologies (ICESC).
  55. Raj, R., & Kos, A. (2022). A comprehensive study of  optical  character  recognition.Proceed-ings  of  the  International  Conference  on Mixed  Design  of  Integrated  Circuits  and Systems.
  56. Reyes, R. C., Cepe, E. M., Guerrero, N. D., Sevilla, R.  V.,  &  Montesines,  D.  L.  (2021). Deep  in-ference   localization   approach   of   license plate  recognition:  A  2014  series  Philippine vehicle  license  plate.Proceedings  of  the 2021 International Conference on Compu-tational Intelligence and Knowledge Econ-omy (ICCIKE).
  57. Reddy,  P.  K.  (2021). Survey  of  classification models  for  secure  image  retrieval:  Signal processing  and  cryptographic  techniques.Journal of Cryptographic Engineering.
  58. Safaldin, M., Zaghden, N., & Mejdoub, M. (2024). An improved YOLOv8 to detect moving ob-jects.IEEE Access.Saha,  S.  (2019). A  review  on  automatic  license plate  recognition  system.arXiv  preprint arXiv:1905.05267.
  59. Singh,   M.,   Sinha,   A.,   &   Krishnamurthy,   B. (2018). Neural  Networks  in  Adversarial Setting  and  Ill-Conditioned  Weight  Space. arXiv preprint arXiv:1801.00905Juliano et al., 2025 /Automated Vehicle Access Control System Utilizing Computer Vision-Based License Plate RecognitionIJMABER 1977Volume 6 | Number 4| April| 2025
  60. Shashirangana, J., Padmasiri, H., Meedeniya, D., &  Perera,  C.  (2021). Automated  license plate recognition: A survey on methods and techniques.IEEE Access.
  61. Shah, P. R., (2013). Image Based Authentication System. International Conference on Com-munication Technology 2013.
  62. Su, Y.-M., Peng, H.-W., Huang, K.-W., & Yang, C.-S. (2019). Image processing technology for text recognition.International Conference on Technologies and  Applications of  Arti-ficial Intelligence.
  63. Suhail,  A.,  Jayabalan,  M.,  &  Thiruchelvam,  V. (2020). Convolutional    Neural    Network Based Object Detection: A Review.
  64. Tenzin,  S.,  Dorji,  P.,  Subba,  B.,  &  Tobgay,  T. (2020). Smart  check-in  check-out  system for  vehicles  using  automatic  number  plate recognition.International  Conference  on Computing Communication and Network-ing Technologies.
  65. Tas, S., Sari, O., Dalveren, Y., Pazar, S., Kara, A., & Derawi,  M.  (2022). Deep  learning-based vehicle  classification  for  low  quality  im-ages.Italian  National  Conference  on  Sen-sors.
  66. Thakur,  N.,  &  Maheshwari,  D.  (2017). A  review of  image  classification  techniques.Seman-tic Scholar.
  67. Terven,  J.  (2023). YOLOv8  in  robotics  and  driv-erless    cars:    Real-time    object    detection system.International  Journal  of  Robotics and Autonomous Systems.
  68. Ugwu, M., Nwiabu, N., & Taylor, O.E., (2022). An Improved Visual Attention Model for Auto-mated    Vehicle    License    Plate    Number Recognition Using Computer Vision.
  69. Vallikannu, R., Kanth, K., Kumar, L., Monisha, & Karthik.   (2022). Vehicle   entry   manage-ment system using image processing.Intel-ligent Systems Reference Library.
  70. Wang, J. (2023). A study of the OCR development history   and   directions   of   development.Highlights   in   Science   Engineering   and Technology.
  71. Wang,  Y.  (2023). Optimization  of  YOLOv8  for UAV  aerial  photography.Journal  of  Un-manned Aerial Systems.
  72. Wang, Y. (2023). YOLOv8 in UAV aerial photog-raphy:  Optimized  for  small  object detec-tion.Journal of Unmanned Aerial Systems.
  73. Yan,  S.  (2019). Security  analysis  and  classifica-tion of image secret sharing: Identifying se-curity  levels  and  analyzing  schemes. Jour-nal of Information Security.
  74. Zhang, Y. (2023). Assessing the security of image classification   models   using   the   Analytic Network  Process  and  Technique  for  Order Preference  by  Similarity  to  an  Ideal  Solu-tion. Journal of Security Engineering.

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