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Fusion: Practice and Applications
Volume 6 , Issue 2, PP: 50-56 , 2021 | Cite this article as | XML |PDF


Automatic Number plate detection for law enforcement using optical recognition system

Authors Names :   Meenu Gupta   1 *     Rakesh Kumar   2     Arpit Sood   3     Gagandeep Kaur   4     Shikha Rastogi   5  

1  Affiliation :  Chandigarh University Punjab, INDIA

    Email :  meenu.e9406@cumail.in

2  Affiliation :  Chandigarh University Punjab, INDIA

    Email :  rakesh.e8623@cumail.in

3  Affiliation :  Chandigarh University Punjab, INDIA

    Email :  arpitsood2000@gmail.com

4  Affiliation :  Chandigarh University Punjab, INDIA

    Email :  gagandeep.4421@cgc.edu.in

5  Affiliation :  Bharati Vidyapeeth College of Engineering, New Delhi, INDIA

    Email :  shikha.bvcoe@gmail.com

Doi   :   https://doi.org/10.54216/FPA.060202

Received April 13, 2021 Accepted September 03, 2021

Abstract :

 Automatic Number Plate Recognition (ANPR) is a specialized type of Optical Character Recognition System (OCR). It is a method of reading a vehicle's license plate using OCR to create vehicle registry or location data. ANPR is utilized by a variety of agencies around the world to enforce the law, including determining whether a vehicle is registered or not. Government entities, such as highway agencies, can categorize traffic movements for computerized toll collection. Images of the text from the license plate can be stored and processed using the ANPR system. Infrared cameras are often employed to take photographs in any lighting condition, whether it is day or night. To be more accurate ANPR technology should also consider plate variations from place to place.

Keywords :


ANPR; OCR (Optical Character Recognition); AI; License Plate Detection (LPD); Social Security Administration (SSA); ASCII (American Standard Code for Information Interchange).

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Cite this Article as :
Meenu Gupta , Rakesh Kumar , Arpit Sood , Gagandeep Kaur , Shikha Rastogi, Automatic Number plate detection for law enforcement using optical recognition system, Fusion: Practice and Applications, Vol. 6 , No. 2 , (2021) : 50-56 (Doi   :  https://doi.org/10.54216/FPA.060202)