How does the machine vision system transmit information to the outside?

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【概要描述】Machine vision is an important branch of artificial intelligence with rapid development. In short, it is to use sensors to replace human eyes for detection and judgment. For robots, the unstructured environment mainly refers to the natural environment of farmland. There are many uncertain factors in the unstructured environment of robot operation, such as the changeable natural light, the complex and changeable working space, the diverse posture of working objects, and the mutual occlusion of branches, leaves and fruits, which have become the technical difficulties of information visual perception in robot operation. The vision system is the eye of the robot operating equipment, is the external sensor and information source, and has the advantages of rich perception information and complete information collection. The visual product converts the captured target into an image signal and transmits it to a special image processing system. The system obtains the shape information of the target, and then converts the pixel distribution, brightness and color information into digital signals. The image processing system then performs various operations on these signals to extract the target characteristics, and then controls the action of the field equipment according to the discrimination results. At present, the work information perception technology based on machine vision has become the key technology and research hotspot of agricultural robot intelligence. The most basic feature of vision system is that it can improve the flexibility and intelligence of production. In some dangerous working environments that are not suitable for manual operation or where artificial vision is difficult to meet the requirements, machine vision is often used to replace artificial vision. At the same time, in large-scale and repeated industrial production processes, machine vision technology can greatly improve production efficiency and automation. Because the target of agricultural robot is discrete individual, and its individual characteristics are random and diverse, this non-standard target information increases the difficulty of perception and judgment of agricultural robot machine vision system. Only by having accurate recognition of the working object and accurate perception of the target position can the machine vision system reduce the damage to the working object and improve the success rate and efficiency of the work.

Machine vision is an important branch of artificial intelligence with rapid development. In short, it is to use sensors to replace human eyes for detection and judgment. For robots, the unstructured environment mainly refers to the natural environment of farmland. There are many uncertain factors in the unstructured environment of robot operation, such as the changeable natural light, the complex and changeable working space, the diverse posture of working objects, and the mutual occlusion of branches, leaves and fruits, which have become the technical difficulties of information visual perception in robot operation.
The vision system is the eye of the robot operating equipment, is the external sensor and information source, and has the advantages of rich perception information and complete information collection. The visual product converts the captured target into an image signal and transmits it to a special image processing system. The system obtains the shape information of the target, and then converts the pixel distribution, brightness and color information into digital signals. The image processing system then performs various operations on these signals to extract the target characteristics, and then controls the action of the field equipment according to the discrimination results.
At present, the work information perception technology based on machine vision has become the key technology and research hotspot of agricultural robot intelligence. The most basic feature of vision system is that it can improve the flexibility and intelligence of production. In some dangerous working environments that are not suitable for manual operation or where artificial vision is difficult to meet the requirements, machine vision is often used to replace artificial vision. At the same time, in large-scale and repeated industrial production processes, machine vision technology can greatly improve production efficiency and automation.
Because the target of agricultural robot is discrete individual, and its individual characteristics are random and diverse, this non-standard target information increases the difficulty of perception and judgment of agricultural robot machine vision system. Only by having accurate recognition of the working object and accurate perception of the target position can the machine vision system reduce the damage to the working object and improve the success rate and efficiency of the work.

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