Critical Challenges In Indian License Plate Recognition: Issues In Pre-Processing, Segmentation, And Recognition

Abstract

Automatic license plate recognition (ALPR) is required to make India smarter, improve law enforcement and make toll easier to collect tolls. Changes in the environment, fonts, oclusation and plates make things very difficult. This study examines many important issues related to early processing, division and understanding of Indian vehicle plate identity. The main targets are to find mistakes in the system and to improve algorithm. The recognition method works very well, using Convenable Neural Network (CNN), photo improvement, fuzzy thresholding and deep automatic separation. The experimental results demonstrate that more challenging conditions enhance accuracy, hence reducing segmentation mistakes and augmenting OCR performance. The discussions focus on traffic automation, security surveillance, and smart city initiatives. Future research should primarily focus on scalable solutions for real-time edge computing.