Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 08, August 2024

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

Licence Plate Recognition System Using Open-CV and Tesseract OCR Engine

Author : Rithik B 1 Raghav G 2 Harshith M 3 Rahul Patwadi 4 Aravind H S 5

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Date of Publication :12th September 2022

Abstract: As the technology has taken a leap to make sure human lives get easier, it has also come with certain consequences. One of them being traffic control and vehicle owner identification has really become a serious issue in the 21st century. Due to the advancements in automobile technology, it is very easy for a person to violate traffic rules and it is practically not possible for humans to stop or have a track record of the vehicles’ number plate travelling at higher speeds. This is a major problem which is being faced by developing countries and our paper will discuss an implementable solution for this problem. Licence plate recognition (LPR) is an information processing system which performs an optical character recognition (OCR) on a digital image of the licence plate which consists of alpha-numeric characters. In this paper we put forward three staged licence plate recognition system based on open-cv and tesseract OCR engine which consists of licence plate detection, character segmentation and character recognition. The system generally uses infrared (IR) illumination to allow the camera to capture images at any point of the day. It also performs various functions such as capturing the image of the vehicle, storing the captured image along with the transcript of the licence plate. Open cv plays an important role in preparing images and videos to identify objects and tesseract OCR is used for text recognition in our prototype. The main purpose of this system is to design and develop an accurate image processing method along with successful recognition of the alphanumeric characters.

Reference :

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    2. Jameson, H. S. Abdullah, S. Norul, A. N. Ghazali, N. Nur, and N. A.Zamani, "Multiple Frames Combination Versus Single Frame Super Resolution Methods for CCTV Forensic Interpretation," Journal of Information Assurance & Security, vol. 8, 2013.
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    4. Ragini Bhat, Bijender Mehandia,” Recognition of vehicle number plate using matlab”, International journal of innovative research in electrical, electronics, instrumentation and control engineering vol. 2, issue 8, august 2014.
    5. Cheng-Hung Lin , Yong-Sin Lin , and Wei-Chen Liu, An efficient license plate recognition system using convolution neural networks. 2018 IEEE International Conference on Applied System Invention
    6. R. Girshick, F. Iandola, T. Darrell, J. Malik, Deformable Part Models are Convolutional Neural Networks. arXiv preprint arXiv:1409.5403, 2014. in CVPR, 2015.
    7. S. Du, M. Ibrahim, M. Shehata, and W. Badawy. Automatic license plate recognition (alpr): A state-of-the-art review. Circuits and Systems for Video Technology, IEEE Trans. on, 23(2):311- 325, 2013.
    8. W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.- Y. Fu, and A. C. Berg. Ssd: Single shot multibox detector. In European Conference on Computer Vision, pages 21–37. Springer, 2016
    9. Davix, X.A., Christopher, C.S., Christine, S.S. (2017) License plate detection using channel scale space and colour-based detection method. IEEE International Conference on Circuits and Systems (ICCS). In: Thiruvananthapuram, India. 82-6.
    10. A. Abd., Sun, SL., Fu, M.X., Sun, H., I, Khan. (2019) License Plate Segmentation Method Using Deep Learning Techniques. In: Signal and Information Processing, Networking and Computers. 4th International Conference on Signal and Information Processing, Networking and Computers (ICSINC). Qingdao, China. pp. 58-65.
    11. Mei Yu and Yong Deak Kim, “An approach to Korean license plate recognition based on vertical edge matching,” IEEE International Conference on System, Man and Cybernetics, 2000, vol.4, pp. 2975-2980.
    12. Gisu Heo, Minwoo Kim, Insook Jung, Duk Ryong Lee, Il Seok Oh, “Extraction of car license plate regions using line grouping and edge density methods,” International Symposium on Information Technology Convergence, 2007, pp.37-42
    13. Sanap, P. R.; Narote, S. P.; Patel, R. B.; Singh, B. P. (2010). AIP Conference Proceedings [AIP INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN SCIENCE AND TECHNOLOGY (ICM2ST-10) - Chandigarh, (India) (25–26 December 2010)] - License Plate Recognition System for Indian Vehicles.
    14. 2016 International Conference on Information and Communication Technology (ICICTM), 16th - 17th May 2016, Kuala Lumpur, Malaysia “A Review on License Plate Recognition System Algorithms” Muayad Ali Hamood Bakhtan, Dr. Munaisyah Abdullah, Dr. Aedah Abd Rahman
    15. A Review Paper on License Plate Recognition System Shally Gupta*, Rajesh Singh, H.L. Mandoria International Journal of Innovative Research in Computer and Communication Engineering 2020 Vol 5 No 1.4
    16. LPRNet: License Plate Recognition via Deep Neural Networks 27 Jun 2018 Sergey Zherzdev, Alexey Gruzdev.

    1. Tella pavani and DVR Mohan “Number Plate Recognition by using open CV- Python”, International Research Journal of Engineering and Technology (IRJET), Volume: 06 Issue: 03 | Mar 2019.
    2. Jameson, H. S. Abdullah, S. Norul, A. N. Ghazali, N. Nur, and N. A.Zamani, "Multiple Frames Combination Versus Single Frame Super Resolution Methods for CCTV Forensic Interpretation," Journal of Information Assurance & Security, vol. 8, 2013.
    3. N.Vishwanath,S.Somasundaram, M.R. Rupesh Ravi, N. Krishnan Nallaperumal,” Connected Component Analysis for Indian License Plate Infra-Red and Color Image Character Segmentation”, IEEE International Conference on Computational Intelligence and Computing Research, 2012.
    4. Ragini Bhat, Bijender Mehandia,” Recognition of vehicle number plate using matlab”, International journal of innovative research in electrical, electronics, instrumentation and control engineering vol. 2, issue 8, august 2014.
    5. Cheng-Hung Lin , Yong-Sin Lin , and Wei-Chen Liu, An efficient license plate recognition system using convolution neural networks. 2018 IEEE International Conference on Applied System Invention.
    6. R. Girshick, F. Iandola, T. Darrell, J. Malik, Deformable Part Models are Convolutional Neural Networks. arXiv preprint arXiv:1409.5403, 2014. in CVPR, 2015.
    7. S. Du, M. Ibrahim, M. Shehata, and W. Badawy. Automatic license plate recognition (alpr): A state-of-the-art review. Circuits and Systems for Video Technology, IEEE Trans. on, 23(2):311- 325, 2013.
    8. W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.- Y. Fu, and A. C. Berg. Ssd: Single shot multibox detector. In European Conference on Computer Vision, pages 21–37. Springer, 2016.
    9. Davix, X.A., Christopher, C.S., Christine, S.S. (2017) License plate detection using channel scale space and colour-based detection method. IEEE International Conference on Circuits and Systems (ICCS). In: Thiruvananthapuram, India. 82-6.
    10. A. Abd., Sun, SL., Fu, M.X., Sun, H., I, Khan. (2019) License Plate Segmentation Method Using Deep Learning Techniques. In: Signal and Information Processing, Networking and Computers. 4th International Conference on Signal and Information Processing, Networking and Computers (ICSINC). Qingdao, China. pp. 58-65.
    11. Mei Yu and Yong Deak Kim, “An approach to Korean license plate recognition based on vertical edge matching,” IEEE International Conference on System, Man and Cybernetics, 2000, vol.4, pp. 2975-2980.
    12. Gisu Heo, Minwoo Kim, Insook Jung, Duk Ryong Lee, Il Seok Oh, “Extraction of car license plate regions using line grouping and edge density methods,” International Symposium on Information Technology Convergence, 2007, pp.37-42
    13. Sanap, P. R.; Narote, S. P.; Patel, R. B.; Singh, B. P. (2010). AIP Conference Proceedings [AIP INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN SCIENCE AND TECHNOLOGY (ICM2ST-10) - Chandigarh, (India) (25–26 December 2010)] - License Plate Recognition System for Indian Vehicles.
    14. 2016 International Conference on Information and Communication Technology (ICICTM), 16th - 17th May 2016, Kuala Lumpur, Malaysia “A Review on License Plate Recognition System Algorithms” Muayad Ali Hamood Bakhtan, Dr. Munaisyah Abdullah, Dr. Aedah Abd Rahman
    15. A Review Paper on License Plate Recognition System Shally Gupta*, Rajesh Singh, H.L. Mandoria International Journal of Innovative Research in Computer and Communication Engineering 2020 Vol 5 No 1.4
    16. LPRNet: License Plate Recognition via Deep Neural Networks 27 Jun 2018 Sergey Zherzdev, Alexey Gruzdev.

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