Machine vision primarily uses computers to simulate human visual functions, extracting information from images of objective things, processing and understanding it, and ultimately using it for practical detection, measurement, and control. The biggest characteristics of machine vision technology are high speed, large information capacity, and multiple functions.
What is machine vision technology?
01. Introduction to the Concept
Machine vision primarily uses computers to simulate human visual functions, but it is not merely a simple extension of the human eye. More importantly, it possesses some of the functions of the human brain—extracting information from images of objective things, processing and understanding it, and ultimately using it for practical detection, measurement, and control.
02. System Advantages
Applying machine vision technology to poultry egg quality inspection has unparalleled advantages over manual inspection. Surface defects, size, and shape are important characteristics of egg quality. Using machine vision for inspection not only eliminates the interference of subjective human factors but also provides quantitative descriptions of these indicators, avoiding human-influenced inspection results, reducing inspection and grading errors, and improving productivity and grading accuracy.
03. System Composition
A typical industrial machine vision application system includes digital image processing technology, mechanical engineering technology, control technology, light source illumination technology, optical imaging technology, sensor technology, analog and digital video technology, computer hardware and software technology, human-machine interface technology, etc.
04. Technical Analysis
"Machine vision" refers to using machines to replace human eyes for measurement and judgment.
A machine vision system refers to a system that uses machine vision products (i.e., image acquisition devices, which can be either CMOS or CCD) to capture images, then transmits the images to a processing unit. Through digital processing, the system determines dimensions, shapes, colors, and other characteristics based on pixel distribution, brightness, color, and other information. The system then controls the actions of equipment on-site based on the determination results.
05. Applications and Impacts
With the development of computer technology and fieldbus technology, machine vision technology has become increasingly mature and has become an indispensable product in modern processing and manufacturing industries. It is widely used in food and beverage, cosmetics, pharmaceuticals, building materials and chemicals, metal processing, electronics manufacturing, packaging, automobile manufacturing and other industries.
The introduction of machine vision has replaced traditional manual inspection methods, greatly improving the quality of products launched to the market and increasing production efficiency.
Because machine vision systems can rapidly acquire large amounts of information, are easily processed automatically, and are readily integrated with design and manufacturing control information, they are widely used in modern automated production processes for areas such as condition monitoring, finished product inspection, and quality control. The key feature of machine vision systems is improved production flexibility and automation. In hazardous working environments unsuitable for manual labor or where human vision is insufficient, machine vision is often used to replace manual vision. Furthermore, in large-scale industrial production, manual inspection of product quality is inefficient and lacks precision; machine vision inspection methods can significantly improve production efficiency and automation. Moreover, machine vision facilitates information integration, making it a fundamental technology for computer-integrated manufacturing.
Machine vision is an engineering field that integrates mechanics, optics, electronics, and software systems to inspect natural objects and materials, as well as man-made defects and manufacturing processes. It aims to detect defects, improve quality, increase operational efficiency, and ensure product and process safety. It is also used to control machines.
