Pattern recognition and computer vision differ in their focus and scope. Pattern recognition deals with identifying regularities or patterns in data, such as detecting handwritten digits or classifying speech signals. It focuses on algorithms and statistical methods to recognize patterns in various data types.
Computer vision specifically focuses on interpreting visual data, aiming to replicate human vision by understanding images and videos. Tasks like object detection, facial recognition, and image segmentation are examples of computer vision applications.
While computer vision often uses pattern recognition as a core technique, it is broader, incorporating additional elements like spatial understanding and temporal analysis in video data.