• Yashika Dhanwani
• M. P. Borawake
• Rajashri Kunale
• Namrata Vyavahare
• Priyanka Vyavahare

Most vehicle license plate recognition uses neural network techniques to enhance its computing capability. The image of the vehicle license plate is captured and processed to produce a textual output for further processing. This paper reviews image processing and neural network techniques applied at different stages which are pre-processing, filtering, feature extraction, segmentation and recognition in such way to remove the noise of the image, to enhance the image quality and to expedite the computing process by converting the characters in the image into respective text. License plate recognition can be better solved by solutions with settings oriented for different applications. Numerous techniques have been developed for LPR in still images or video sequences, and the purpose of this project is to assess and implement them as a real-world solution. This Project aims at making the databases obtained available for usage in an application for a parking system wherein the detected License plate number is matched with the pre-existing user information. This enables the application to detect the amount of time for which the vehicle was parked and generate a digital bill to the user accordingly. The experimental results show that the proposed method not only locates license plates accurately but also be robust to scenes of illumination variation, noise distortion, and blurry effects.

Optical character recognition (OCR), image processing, License plate recognition (LPR), Segmentation, pre-processing, filtering, feature extraction.

"License Plate Recognition Based Mobile Application For Parking Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.d599-d603, November-2022, Available :http://www.jetir.org/papers/JETIR2211383.pdf

"License Plate Recognition Based Mobile Application For Parking Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppd599-d603, November-2022, Available at : http://www.jetir.org/papers/JETIR2211383.pdf