Parking violation detection and monitoring system using image processing and deep learning

• Main Authors: Das, Samriddho, Revathi, M.
• Format: Conference Proceeding
• Language: English
• Subjects: Equalization; Histograms; Image processing; Night; Object motion; Parking violations
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0222344

To take out precise ROIs and improve images for precise night-time vehicle number plate detection, we combine a brand-new area of interest (ROI) extraction technique based on improved multi-scale retinex with a method for improving night time images that combines object recommendations with vehicle light detection. (MSR). A suggested score-level feature fusion unifies five complementing traits. The approach we provide can find moving objects that are blurry or partially obscured, as well as moving objects of different shapes, sizes, numbers, positions, and backdrops. The use of a licence plate detection (LPD) system is essential in a variety of traffic-related applications. This project aims to create a sophisticated detecting system that excels in challenging situations. It suggests a reliable preprocessing improvement technique for correctly identifying licence plates in challenging vehicle photos. The suggested approach combines a Gaussian filter with a contrast-limited adaptive histogram equalisation methodology and an enhanced cumulative histogram equalisation method, the local binary pattern and the histogram of an orientated gradient. We identify names using the licence plate. Eventually, we see outcomes. Using the voice command, DON’T PARK IN THIS AREA to send an SMS to the number that is saved in the database. This object has a penalty of this exact amount if it is not obeyed.