Computer vision and image recognition is a transformative field of artificial intelligence that allows machines to understand and interpret visual information. These technologies have far-reaching applications, from improving the safety of autonomous vehicles to revolutionizing robotics. In this post, we’ll delve deeper into the field of computer vision, exploring image recognition techniques and exploring their key role in autonomous vehicles and robotics.
At its core, computer vision aims to enable computers to process, interpret and understand visual information from the world, much like human vision. It includes tasks such as image analysis, object detection, tracking and scene understanding.
Image recognition is a subset of computer vision that aims to identify and classify objects or patterns in images or videos. To perform these tasks, it uses machine learning algorithms, particularly deep learning models.
Object detection and classification
Computer vision and image recognition are fundamental to the safe operation of autonomous vehicles. These technologies enable vehicles to detect and classify objects in their environment, such as pedestrians, other vehicles, road signs and traffic lights.
Lane detection and tracking
Image recognition techniques are used to detect lane markings and track the position of a vehicle within a lane. This is critical for lane maintenance and autonomous navigation.