C/C++ software using OpenCV
Budget: ₹75,000 – ₹150,000 INR
Develop a C/C++ software using OpenCV to detect vehicles, human attributes, and traffic violations with day, low-light, and night vision capabilities.
1. Track and log any identified traffic violations by the vehicle.
Detect vehicle and track its movement.
Identify vehicle type (e.g., bike, car, lorry, truck).
Recognize vehicle brand (e.g., Toyota, Honda).
Detect vehicle color.
Measure and record vehicle speed.
Capture vehicle license plate text and image.
Extract visible text on the vehicle (e.g., company names, slogans).
2. Human Detection in Vehicles
Count the number of people in the vehicle.
Detect helmet and seatbelt presence for driver and passengers.
Capture and recognize driver and passenger faces.
Record possible human features such as gender and race.
3. Traffic Violation Detection
Detect yellow line crossing.
Identify red light violations.
Monitor pedestrian crosswalk violations.
Detect vehicles moving in the wrong direction.
Detect and record over-speeding.
Identify vehicles parked in no-parking zones.
Detect vehicles driving on or over zebra crossings.
Requirements:
Environment: Should function effectively in daylight, low light, and at night (night vision support).
Scope: This is a large-scale project. High-quality results may lead to additional features and projects.
Controller: Raspberry pi
Deliverable:
Working version source code with high quality results
1. Track and log any identified traffic violations by the vehicle.
Detect vehicle and track its movement.
Identify vehicle type (e.g., bike, car, lorry, truck).
Recognize vehicle brand (e.g., Toyota, Honda).
Detect vehicle color.
Measure and record vehicle speed.
Capture vehicle license plate text and image.
Extract visible text on the vehicle (e.g., company names, slogans).
2. Human Detection in Vehicles
Count the number of people in the vehicle.
Detect helmet and seatbelt presence for driver and passengers.
Capture and recognize driver and passenger faces.
Record possible human features such as gender and race.
3. Traffic Violation Detection
Detect yellow line crossing.
Identify red light violations.
Monitor pedestrian crosswalk violations.
Detect vehicles moving in the wrong direction.
Detect and record over-speeding.
Identify vehicles parked in no-parking zones.
Detect vehicles driving on or over zebra crossings.
Requirements:
Environment: Should function effectively in daylight, low light, and at night (night vision support).
Scope: This is a large-scale project. High-quality results may lead to additional features and projects.
Controller: Raspberry pi
Deliverable:
Working version source code with high quality results