1. Introduction:
Computer vision is a combination of image processing, pattern recognition, and artificial intelligence techniques, focusing on computer analysis of one or more images.
Machine vision focuses on the engineering of computer vision technology, which can automatically acquire and analyze specific images to
control corresponding behaviors. Computer vision provides the theoretical and algorithmic basis of image and scene analysis for machine vision, and machine vision provides sensor models, system construction and implementation means for the realization of computer vision.
Machine vision systems are generally computer-centric, mainly composed of visual sensors, high-speed image acquisition systems and special image processing systems.
Vision sensors are the direct source of information, consisting mainly of one or two image sensors, and sometimes light projectors and other equipment. Its main function is to obtain enough raw images for the machine vision system.
The high-speed image acquisition system is composed of a dedicated video decoder, an image buffer and a control interface circuit. Convert the analog video signal acquired by the visual sensor into a digital image signal in real time, and directly transmit the image to the computer for display and processing, or transmit the digital image to a dedicated image processing system for real-time front-end processing of the visual signal.
Three levels of visual system research
1. Computational theory What is the purpose of computation and why it is calculated in this way
2. Expression and algorithm How to implement computational theory, what is input/output expression, and what algorithm is used to realize the conversion between expressions
3. How to implement hardware Physically implement expressions and algorithms, what are the specifics of computational structures.
Three stages of visual information processing:
early visual processing - (element map) mid-term visual processing - (2.5-dimensional map) late visual processing - (3D description)
Computer vision is a combination of image processing, pattern recognition, and artificial intelligence techniques, focusing on computer analysis of one or more images.
Machine vision focuses on the engineering of computer vision technology, which can automatically acquire and analyze specific images to
control corresponding behaviors. Computer vision provides the theoretical and algorithmic basis of image and scene analysis for machine vision, and machine vision provides sensor models, system construction and implementation means for the realization of computer vision.
Machine vision systems are generally computer-centric, mainly composed of visual sensors, high-speed image acquisition systems and special image processing systems.
Vision sensors are the direct source of information, consisting mainly of one or two image sensors, and sometimes light projectors and other equipment. Its main function is to obtain enough raw images for the machine vision system.
The high-speed image acquisition system is composed of a dedicated video decoder, an image buffer and a control interface circuit. Convert the analog video signal acquired by the visual sensor into a digital image signal in real time, and directly transmit the image to the computer for display and processing, or transmit the digital image to a dedicated image processing system for real-time front-end processing of the visual signal.
Three levels of visual system research
1. Computational theory What is the purpose of computation and why it is calculated in this way
2. Expression and algorithm How to implement computational theory, what is input/output expression, and what algorithm is used to realize the conversion between expressions
3. How to implement hardware Physically implement expressions and algorithms, what are the specifics of computational structures.
Three stages of visual information processing:
early visual processing - (element map) mid-term visual processing - (2.5-dimensional map) late visual processing - (3D description)