The Connection and Difference of Artificial Intelligence, Machine Vision and Computer Vision






What technologies does machine vision include?

Machine vision is a comprehensive technology, including image processing, mechanical engineering technology, control, light source lighting, optical imaging, sensors, analog and digital video technology, computer software and hardware technology (image enhancement and analysis algorithm, image card, I/O card, etc.).


In our daily work, we often hear professional terms such as artificial intelligence, machine learning, computer vision, image processing, pattern recognition and so on. We don't know the specific meaning or whether it has something to do with machine vision. Today's edition will summarize the meanings and differences of artificial intelligence, machine learning, computer vision, image processing and pattern recognition.



Industrial Application of Machine Vision

Simply put, machine vision is to use machines instead of human eyes to measure and judge. Machine vision system is to convert the captured object into image signal through machine vision products (i.e. image capturing device, divided into CMOS and CCD) and transmit it to a special image processing system to obtain the shape information of the captured object, and convert it into digital signal according to the information of pixel distribution, brightness and color. The image system extracts the characteristics of the target by various operations on these signals. Then, according to the result of discrimination, the device action on the spot can be controlled.



Essence of Artificial Intelligence

The basic idea and content of artificial intelligence. That is to say, artificial intelligence is to study the law of human intelligence activities, construct an artificial system with certain intelligence, and study how to make computers complete the work that needed human intelligence to be competent in the past. That is to say, to study how to apply computer software and hardware to simulate some basic theories, methods and technologies of human intelligent behavior. Artificial intelligence is essentially a simulation of the information process of human thinking.



The Essence of Machine Learning

Machine learning is to study how computer simulates or realizes human learning behavior in order to acquire new knowledge or skills, reorganize existing knowledge structure and continuously improve its performance. It is the core of artificial intelligence and the fundamental way to make computers intelligent. It is applied in all fields of artificial intelligence. It mainly uses induction, synthesis rather than deduction. It is a simulation of human learning behavior.


Computer Vision: The ability to acquire and process information by simulating human visual mechanism with a computer. It is a simulation of human vision.

The research object of computer vision is mainly three-dimensional scene mapped to single or multiple images, such as reconstruction of three-dimensional scene. The research of computer vision focuses on the content of image to a great extent.


Image processing: Image processing technology converts the input image into another image with desired characteristics. For example, the output image can be processed to have a higher signal-to-noise ratio, or the details of the image can be highlighted by the enhancement process, so as to facilitate the operator's inspection. In computer vision research, image processing technology is often used for preprocessing and feature extraction.


The research object of image processing and image analysis is mainly two-dimensional image to realize image transformation, especially for pixel-level operations, such as improving image contrast, edge extraction, noise removal and geometric transformation such as image rotation. This feature shows that the research content of image processing and image analysis has nothing to do with the specific content of the image.


Pattern Recognition: The pattern recognition technology divides the image into certain categories according to the statistical characteristics or structural information extracted from the image. For example, text recognition or fingerprint recognition. In computer vision, pattern recognition technology is often used to recognize and classify some parts of an image, such as segmentation regions.

Pattern recognition uses various methods to extract information from signals, mainly using statistical theory. One of the main directions in this field is to extract information from image data.







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