"Machine Vision Application" Application of machine vision and vision sensors

In industrial environments, machine vision applications are becoming increasingly mature and play a major role in improving the flexibility and automation of industrial production. In addition, in dangerous working environments or situations where artificial vision cannot meet the requirements, using machine vision to replace artificial vision also improves the safety of operations. The image recognition system that uses image recognition technology to detect product appearance defects, label printing errors, and circuit board welding quality defects on the assembly line is a successful example of the application of machine vision systems in the industrial field. Printing and packaging, automobile industry, semiconductor materials, food production, etc. are all application directions of machine vision in the industrial field.

For example, in agricultural production, part of the work is to judge the appearance of crops or agricultural products, such as fruit quality testing, fruit maturity judgment, crop growth status, and weed identification, etc. These tasks that used to mainly rely on human vision for identification and judgment can be partially or completely replaced by machine vision technology, thereby realizing agricultural automation and intelligence. For example, Huang Xiuling's team from Nanjing Forestry University designed an intelligent grading production line that can dynamically and real-time detect apple quality. On the production line, three evenly distributed cameras collect surface information of apples at one time, and the computer intelligent control system conducts a comprehensive analysis of the collected information to grade the apples. However, some experts said that due to the complex variability and unstructured characteristics of the farmland environment, the current application of machine vision in agricultural production is not yet mature and needs further improvement.

In processes such as exploration and collection and non-ferrous smelting, machine vision technology also has great potential. Ore dressing is an important link in the processing of mineral resources, and the level of mineral processing directly affects the recovery of mineral resources. In recent years, mineral surface feature monitoring technology based on machine vision has attracted great attention from scientific research institutions in industrialized countries. Data show that the European Union, in conjunction with a number of universities and enterprises, launched the "Bubble Structure and Color Characterization Based on Machine Vision" project in 2000; South Africa, Chile and other countries have also applied machine vision to the flotation monitoring of graphite and platinum metals. Domestically, research on flotation monitoring of coal and nickel has also made significant progress.

Applications of machine vision and vision sensors

Machine vision technology can also be applied to intelligent transportation, security, medical equipment, etc. In the medical field, machine vision can assist doctors in analyzing medical images, such as X-ray fluoroscopy, MRI images, CT images, etc. In the field of scientific research, machine vision can be used for material analysis, biological analysis, chemical analysis and life science analysis, such as automatic classification and counting of blood cells, chromosome analysis, cancer cell identification, etc.