Computer Vision Project : Computer Vision-Based Car Parking Space Monitoring System using OpenCV
In this project, we will develop a computer vision application using OpenCV that can track and monitor car parking spaces. The system will use camera feeds to detect and recognize parking spaces, track the occupancy of each space, and provide real-time updates on the availability of parking spaces.
Project Objectives:
Parking Space Detection: Use OpenCV to detect and recognize parking spaces in a given camera feed.
Occupancy Tracking: Track the occupancy of each parking space and update the status in real-time.
Availability Monitoring: Provide real-time updates on the availability of parking spaces.
Alert System: Implement an alert system to notify users when a parking space becomes available.
Project Methodology:
Camera Feed Acquisition: Acquire camera feeds from a parking lot or a designated area.
Image Preprocessing: Preprocess the camera feed images to enhance quality and remove noise.
Parking Space Detection: Use OpenCV's computer vision techniques (e.g., edge detection, contour detection) to detect and recognize parking spaces.
Occupancy Tracking: Use OpenCV's tracking algorithms (e.g., background subtraction, object tracking) to track the occupancy of each parking space.
Availability Monitoring: Update the status of each parking space in real-time and provide availability information.
Alert System: Implement an alert system using OpenCV's GUI functionality or a separate notification system.
Tools and Technologies:
OpenCV library for computer vision tasks
Python programming language
Camera feed acquisition hardware (e.g., USB camera, IP camera)
Computer or embedded system for processing and analysis