Computer vision is integral to advanced driver-assistance systems (ADAS) and autonomous vehicles. It enables lane detection, traffic sign recognition, pedestrian detection, and collision avoidance. Smart Transportation Systems Revolutionizing Parking, Law Enforcement, Plate Number Recognition, Tolling, and Traffic Monitoring Solutions.

Pedestrian Detection in Traffic.

Pedestrian detection and tracking have become central research areas of computer vision due to their impact on the design of Pedestrian protection systems and smart cities. It uses advanced cameras that automatically capture, identify and locate pedestrians in images or videos on the basis of body attire, position, occlusion, illuminance, and background clutter. This pedestrian detection is vital in autonomous driving, traffic management, and transit safety and efficiency.

Road Condition Monitoring.

 Now that’s a much-needed breakthrough in road infrastructure. It detects defects and assesses the overall road condition by monitoring changes in concrete and asphalt. This automated pavement distress detection has helped in maintaining allocation efficiency and minimizing safety risks related to accidents. Computer vision algorithms use the collected image data and process it to build automatic crack detection and classification system enabling humans to take preventive measures timely.