Object filtering is the process of selecting specific detected objects while ignoring others based on predefined criteria. In computer vision systems, filtering can be performed using characteristics such as object type, size, location, movement, confidence level, or other visual attributes.
For example, a smart surveillance system may detect people, vehicles, animals, and other objects in a camera view but filter the results to focus only on vehicles entering a restricted area. Similarly, an industrial vision system can ignore background elements and concentrate on products moving along a production line. Object filtering helps reduce irrelevant detections, improve processing efficiency, and make AI-based vision systems more focused and accurate.
