Recent Developments in Automatic Number Plate Detection and Recognition

Faraz Imtiyaz Mir; Nibbritta Niloy Sarkar; Yojna Arora; Avinash Kumar Sharma

Abstract

Automatic Number Plate Recognition (ANPR) is a mass surveillance system that captures the image of vehicles and recognizes their license numbers. ANPR can be used in the detection of stolen vehicles. The detection of stolen vehicles can be done in an efficient manner by using the ANPR systems located in the highways. This method presents a recognition method in which the vehicle plate image is obtained by the digital cameras and the image is processed to get the number plate information. An image of a vehicle is captured and processed using image pre-processing algorithm. In this context, the number plate area is localized using edge detection method and the characters acquired are segmented using segmentation method. The segmented characters are passed to Optical character reader (OCR) which gives exact characters of the number plate and are stored in database. The image pre-processing is done using Gaussian Blur method, conversion of RGB (Red, Green, Blue) to grayscale, Edge detection using sobel followed by contour detection and license plate is extracted. OCR is run on the Region of Interest (ROI) given by the contour analysis. The OCR provides the vehicle’s num-ber obtained from the number plate and is stored in the database which is used for surveillance and tracking vehicle’s location. The software used in the process is Python version 3 and different python libraries like Tesseract OCR, OpenCV.

Keywords

Automatic Number Plate Recognition (ANPR), surveillance, image pre-processing, Gaussian Blur method, Optical character reader (OCR).

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Cites this article as

F. I. Mir, N. N. Sarkar, Y. Arora, A. K. Sharma, "Recent Developments in Automatic Number Plate Detection and Recognition", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-12, no.5, pp.28-35, 2024. Available from: https://doi.org/10.55524/ijircst.2024.12.5.5

Corresponding Author

Yojna Arora

Associate Professor, Department of Computer Science Engineering, Sharda University, Greater Noida, India

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