Object recognition is about the identification of objects. In optical object recognition, objects are examined for certain characteristic features, edges, curvatures, proportions or templates, and conclusions are drawn about the object.
In object recognition or object detection( OD), objects are classified by means of image processing and divided into different classes. This involves object identification. It is about segmenting image details and extracting certain image features and capturing the objects from different angles.
As far as object features are concerned, it is about object shape, its size, proportions, color, textures and various other features. In order to recognize an object in an image, it must first be found in the image. Only then can an assignment be made via classification. Object recognition can distinguish between buildings and machines, people and animals, motor vehicles, bicycles and other means of transport. It is used, among other things, in industrial production technology, robotics and autonomous driving. Here alone, there are various possible applications such as pedestrian detection, traffic sign recognition or light signal detection.