Machine Vision (MV) and Computer Vision (CV) are both related and different. Machine vision and computer vision have a lot of similarities, in the architecture is the base layer + technology layer + application layer; And the basic theoretical framework, underlying theory, algorithm and so on are similar, so machine vision and computer vision in the field of technology and application will have a certain overlap.

This article mainly carries on the brief distinction in four aspects

1. Subject classification

Machine vision as a system engineering "discipline", different from computer vision, is a form of computer science foundation.

Computer vision is a computer "science" that involves the theory behind artificial systems that extract information from images. It is interdisciplinary.

2. The degree of information processing

Machine vision is mainly to extract and process relatively shallow image information, computer vision is to extract and process relatively deep image information, so the degree of understanding of the two information is not the same. If machine vision is regarded as the main body of a system, then computer vision is the retina, optic nerve, brain and central nervous system.

3. Application field

Machine vision is the application of computer vision in factory automation. Traditional machine vision is mainly used in industrial fields, such as semiconductors, automobile industry, military, and computer vision is not limited to industrial fields.

Computer vision includes scene reconstruction, scene recognition, object detection, object recognition, video tracking, 3D pose estimation, motion estimation and image restoration.

4, focusing on the

Computer vision is a combination of image processing, pattern recognition and artificial intelligence technology, focusing on the computer analysis of one or more images. Images can be acquired by a single or multiple sensors, or a sequence of images acquired by a single sensor at different times.

Machine vision focuses on computer vision technology engineering, which can automatically acquire and analyze specific images to control the corresponding behavior. Specifically, computer vision provides the theoretical and algorithmic basis of image and scene analysis for machine vision, and machine vision provides sensor model, system construction and implementation means for the realization of computer vision. The two share a set of theoretical system, but the direction of development is different. Machine vision focuses on the practical application in the industrial field, while computer vision focuses on the research of theoretical algorithms.