How OpenCV is Used in the Real World
OpenCV can be used to create 3D models from 2D images and videos using techniques like stereoscopic vision and structure from motion.
OpenCV can be used for tasks like crop health monitoring, yield estimation, and autonomous vehicle guidance in agriculture.
OpenCV can be used to develop augmented reality applications, which overlay digital content onto the real world.
OpenCV can be used to recognize faces in an image or video stream. The process involves identifying regions of the image that contain faces and extracting these regions for further processing.
OpenCV can be used to recognize and interpret human gestures, such as hand movements or facial expressions.
OpenCV can be used to inspect manufactured products for defects, such as cracks, scratches, or misalignments.
OpenCV can be used to detect and recognize various objects in images and videos, such as faces, license plates, and vehicles.
OpenCV can be used to recognize text in images, which can be useful for applications like document scanning and license plate recognition.
OpenCV can be used in robotics for tasks such as object tracking, navigation, and obstacle avoidance.
OpenCV can be used in security systems for tasks like intrusion detection, people counting, and facial recognition.
OpenCV can be used to analyze traffic patterns, detect congestion, and estimate vehicle counts for urban planning and transportation management.
OpenCV can be used in medical imaging to analyze medical images, such as X-rays, MRIs, and CT scans, for diagnosis and treatment planning.
OpenCV can be used to recognize and track objects in images and video