Applications of machine vision intelligence in life are as follows:
Computer vision is used in face recognition, security, agriculture, industry, healthcare, drones and other scenarios.
Computer vision is a study of how to make the machine "see" the science, furthermore, is to refer to the use of cameras and computers instead of the human eye on the target for identification, tracking and measurement of machine vision, and further graphics processing, so that the computer processing to become more suitable for the human eye to observe or transmit to the instrument to detect the image.
As a scientific discipline, computer vision studies related theories and techniques in an attempt to build artificial intelligence systems capable of obtaining 'information' from images or multidimensional data. By information, we mean what Shannon defines as information that can be used to help make a "decision".
Because perception can be thought of as extracting information from sensory signals, computer vision can also be thought of as the science of how to make artificial systems 'perceive' from images or multidimensional data.
Analysis:
Vision is an integral part of a wide range of intelligent/autonomous systems in application areas such as manufacturing, inspection, document analysis, medical diagnostics, and military.
Because of its importance, some advanced countries, such as the United States, have categorized research on computer vision as a major fundamental problem in science and engineering with broad economic and scientific implications, known as a grand challenge. The challenge of computer vision is to develop visual capabilities for computers and robots that are comparable to the human level.
Machine vision requires image signals, texture and color modeling, geometric processing and reasoning, and object modeling. A capable vision system should tightly integrate all of these processes. As a discipline, computer vision began in the early 1960s, but many of the important advances in basic computer vision research were made in the 1980s.
Computer vision is closely related to human vision, and a proper understanding of human vision will be very beneficial to computer vision research. For this reason we will first introduce human vision.