AI-Powered License Plate Recognition

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Year : May 23, 2024 at 4:22 pm | [if 1553 equals=””] Volume :11 [else] Volume :11[/if 1553] | [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] : 01 | Page : 20-29

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Tejas Amrutkar, Amaan Saifi, Sakshi Auti, Prashant Dahale

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  1. Student, Student, Student, Professor Department of Electronics and Telecommunication Engineering, Singhad College of Engineering, Department of Electronics and Telecommunication Engineering, Singhad College of Engineering, Department of Electronics and Telecommunication Engineering, Singhad College of Engineering, Department of Electronics and Telecommunication Engineering, Singhad College of Engineering Maharashtra, Maharashtra, Maharashtra, Maharashtra India, India, India, India
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Abstract

nWith the number of cars multiplying daily, safety precautions are judged required. Automatic number plate recognition uses image processing and machine learning techniques to recognize vehicle numbers. By utilizing the vehicle number plate, the approach recommended seeks to establish a capable automated approved auto identification system. We describe an automated vehicle number detection system based on image processing and Raspberry Pi that reads license plates. In this setting, a Raspberry Pi is linked to a camera. The device continuously examines incoming camera footage for any traces of number plates When it notices a particular number plate in front of the camera, it analyzes the input from the camera and extracts the number tag component from7 the picture. With a Raspberry Pi, the system continuously scans its environment for moving vehicles and instantly analyzes incoming video. The system immediately initiates image processing algorithms to extract and isolate the number plate region from the captured frame upon detecting a vehicle within its field of view. The vehicle number plate region is extracted from an image using OCR, Yolo algorithm through character segmentation. After that, the gathered data is reviewed with the relevant authority dataset to look into precise details like the owner of the car, the place of the vehicle’s registration, the address, and so on.

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Keywords: Number Plate Recognition, Raspberry Pi, Gps Notification, Vibration Sensor, Pressure Sensor

n[if 424 equals=”Regular Issue”][This article belongs to Trends in Machine design(tmd)]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Trends in Machine design(tmd)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article: Tejas Amrutkar, Amaan Saifi, Sakshi Auti, Prashant Dahale. AI-Powered License Plate Recognition. Trends in Machine design. May 23, 2024; 11(01):20-29.

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How to cite this URL: Tejas Amrutkar, Amaan Saifi, Sakshi Auti, Prashant Dahale. AI-Powered License Plate Recognition. Trends in Machine design. May 23, 2024; 11(01):20-29. Available from: https://journals.stmjournals.com/tmd/article=May 23, 2024/view=0

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References

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  1. Aishwarya Agrawal &Nikita Pardakhe,―Automatic License Plate Recognition Using Raspberry Pi‖, International Interdisciplinary Conference on Science Technology Engineering Management Pharmacy and Humanities Held on 22nd–23rd April 2017
  2. Rahul R. Palekar, Sushant U. Parab, Dhrumil P. Parikh, Vijaya N. Kamble, “Real Time License Plate Detection Using OpenCV and Tesseract”, International Conference on Communication and Signal Processing, April 6–8, 2017, India
  3. Abirami, Dr. J.S.Leena Jasmine, ―Accurate Vehicle Number Plate Regognition And Real Time Identification Using Raspberry Pi‖, International Research Journal of Engineering and Technology (IRJET) Volume: 05 Issue: 04, Apr-2018,7.
  4. Parag Parmar, Ashok M.Sapkal, Real time detection and reporting of vehicle collision, IEEE,2017
  5. T. Qadri and M. Asif, “Automatic Number Plate Recognition System for Vehicle Identification Using Optical Character Recognition,” 2009 International Conference on Education Technology and Computer, pp. 335–338, 2009.
  6. Mohanad Hazim Nsaif Al-Mayyahi, Nawaf Hazim Barnouti and Mohammed Abomaali, “Vehicle Detection and License Plate Recognition System” International Journal of Engineering & Technology, 7 (4) (2018) 3170–3174 International Journal of Engineering & Technology Website: www.sciencepubco.com/index.php/IJET, doi: 10.14419,/ijet.v7i4.19154 Research paper, 7
  7. B Mane, Gayatri Bade and Varsha Patil, “Image Processing Based Toll Automation Technique Using ANPR” Helix The Scientific Explorer, Vol. 9 (3): 4926–4930,5, 30th June 2019, DOI: 10.29042/2019-4926-4930
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    Issue: 03.

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Original Research

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Trends in Machine design

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Volume 11
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 01
Received April 17, 2024
Accepted May 3, 2024
Published May 23, 2024

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