Pothole Detection
Early Intervention in Road Maintenance with Computer Vision for Pothole Detection
Maintaining good road conditions is essential to ensure transportation & safe and efficient. Potholes are a major challenge for municipal authorities to improve road quality. By leveraging Computer Vision, authorities can automate the process of identifying and locating potholes, allowing for more efficient repairs and maintenance.
Tackling Challenges of Pothole Detection with Vision AI for Urban Sustainability
Potholes are often addressed manually by human operators, which is costly and inefficient. Automated pothole detection through Computer Vision is cost-effective and efficient.
- Vehicle Damage: Vehicle damage from flat tires, wheel damage, collisions, and major accidents.
- Discomfort Driving: Traveller’s experience uncomfortable driving.
- Infrastructure Maintenance Problems: Maintenance issues with road infrastructure.
- Inefficiency of Manual Visual Inspection: Current method of Road Pothole Detection is inefficient, expensive, and it is not safe.
Upgrading Road Infrastructure with Pothole Detection Using Deep Learning
Our algorithm transforms the process of detecting and repairing potholes and enables authorities to take proactive measures in addressing road maintenance concerns, ensuring the safety and convenience of their communities.
- Image Acquisition: Capture road surface images or footage.
- Preprocessing: Enhance image quality through adjustments and noise reduction.
- Feature Extraction: Analyze images using Edge and texture analysis to identify key features.
- Pothole Classification: Use Deep Learning to distinguish potholes from non-potholes.
- Detection and Localization: Apply trained model to detect and identify potholes in real-time.
Restoring Roadways with Computer Vision for Pothole Detection
Our Computer Vision solution empowers road maintenance teams to promptly identify areas that require urgent attention, simplify repair procedures, and curb the deterioration of road infrastructure.
