Introducing "Platesense," our cutting-edge number plate recognition system that combines the power of YOLOv8, a highly efficient object detection algorithm, with the accuracy of Tesseract, an open-source OCR engine. With Platesense, we have developed an advanced solution for real-time number plate detection and text extraction.
Platesence is an advance number plate recognition system. The advanced number plate recognition system utilizes YOLO for accurate object detection and Tesseract for precise optical character recognition, enabling efficient and reliable extraction of number plate information.
Number plate recognition systems can be used to monitor and manage traffic flow, detect violations such as speeding or running red lights, and provide valuable data for traffic analysis and planning.
Advanced number plate recognition helps law enforcement agencies in identifying stolen vehicles, tracking suspects, and investigating criminal activities by automatically comparing number plate data with databases of wanted vehicles or persons of interest.
Number plate recognition systems are employed in parking facilities for automated entry and exit, ticketless parking, and efficient enforcement of parking regulations.
Advanced number plate recognition enables seamless integration with electronic payment systems, facilitating cashless transactions at fuel stations, drive-through restaurants, and other service points.
Introducing our ANPR Demo Video: Unlocking the Power of Automatic Number Plate Recognition Our ANPR Demo Video showcases the incredible capabilities of our Automatic Number Plate Recognition system.
In this video, we provide a comprehensive overview of how our ANPR technology works and highlight its key features and benefits.
The video begins by presenting real-life scenarios where ANPR can make a significant impact, such as toll collection, parking management, and enhancing security in public spaces. Through engaging visuals and informative narration, we demonstrate how our ANPR system revolutionizes these applications.
*Note: The Model is mostly suitable for backend. For demo purpose the model is deployed in front end. It may take time to load.
ANPR DETECTION
This currently uses Custom YOLOv8 Model + Tesseract.js