Differences and relations between machine vision and computer vision
Machine vision and computer vision are two distinct and related terms.
Machinevision (machinevision) focuses on computer vision technology engineering and can automatically acquire and analyze specific images to control the corresponding behavior. Computervision is a combination of image processing, pattern recognition, and artificial intelligence techniques that focuses on computer analysis of one or more images. Specifically, computer vision provides the theoretical and algorithmic basis for image analysis and scene analysis for machine vision. Machine vision provides a sensor model, system configuration, and implementation means for the realization of computer vision.
In a sense, it can be said that a machine vision system is an image that automatically captures one or more target objects, processes, analyzes, and measures various features of the acquired images, and measures Qualitative analysis and quantitative interpretation to obtain a system of knowledge about the target object and make corresponding decisions.
Machine vision and computer vision belong to different disciplines. Studying machine vision is better for the manufacturing industry to provide more technical support to improve product quality and production efficiency; the purpose of studying computer vision is to bring the light to the computer based on the visual characteristics of human beings, so that it can better replace People who come to work or complete tasks that cannot be accomplished by human beings can greatly increase production efficiency, and at the same time, continue to improve people's quality of life.
In computer vision, the computer is used as a carrier or tool, mainly using a computer's high-efficiency CPU. Because the images are all seen in the vision, and the processing of the images is often time consuming, so the image processing can be completed faster and the time for future control can be gained.
Machine vision is a new type of technology in the field of automation. In simple terms, it is to add a smart eye to the machine, let the machine have visual functions, can see and detect and judge, and can replace traditional manual or simple mechanical fixtures. The principle is to image the product or area to be detected, and then use a dedicated image processing software according to the image information. According to the processing result, the software can automatically determine the position, size, appearance information of the product, and preset according to the human The standard judges whether it is qualified or not, and outputs its judgment information to the executing agency.
Machine vision features include: object location, feature detection, defect determination, target recognition, counting, and motion tracking. It is precisely because the machine vision system can quickly acquire a large amount of information, and it is easy to handle automatically. It is also easy to integrate with design information and processing control information. Therefore, in the modern automated production process, people use machine vision systems widely for condition monitoring. Finished product inspection and quality control.
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Computer vision refers to the use of cameras and computers instead of human eyes to identify, track and measure objects, and realizes human visual functions through computers to sense, recognize, and understand three-dimensional scenes in the objective world. There are usually two types of methods: one is the method of bionics, refers to the structural principle of the human visual system, establishes a corresponding processing module to complete similar functions and work, and the other is an engineering method, starting from the function of analyzing the human visual process. It does not deliberately simulate the internal structure of the human visual system, but only considers the input and output of the system, and adopts any existing feasible means to achieve system functions.
In computer vision, images can be acquired by single or multiple sensors, or they can be image sequences acquired by a single sensor at different times. Then the target object is analyzed and identified, the position and attitude of the target object are determined, and the three-dimensional scene is symbolically described. Explanation. In computer vision research, geometric models and complex knowledge expressions are often used. Model-based matching and search techniques are used. Search strategies often use bottom-up, top-down, hierarchical, and heuristic control strategies.
