Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance in industry. The scope of MV is broad. MV is related to, though distinct from, computer vision.
Application
The primary uses for machine vision are automatic inspection and industrial robot guidance. Common machine vision applications include quality assurance, sorting, material handling, robot guidance, and optical gauging.
1. For automatic PCB inspection.
2. For wood quality inspection
3. Final inspection of sub-assemblies
4. Engine part inspection
5. Label inspection of products
6. Checking medical devices for defects
7. Final inspection cells
8. Robot guidance and checking orientation of components
9. Packaging Inspection
10. Medical vial inspection
11. Food pack checks
12. Verifying engineered components
Methods
Machine vision methods are defined as both the process of defining and creating an MV solution and as the technical process that occurs during the operation of the solution. Here the latter is addressed. As of 2006, there was little standardization in the interfacing and configurations used in MV. This includes user interfaces, interfaces for the integration of multi-component systems and automated data interchange. Nonetheless, the first step in the MV sequence of operation is the acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing. MV software packages then employ various digital image processing techniques to extract the required information and often make decisions (such as pass/fail) based on the extracted information.
Imaging
While conventional (2D visible light) imaging is most commonly used in MV, alternatives include imaging various infrared bands, line scan imaging, 3D imaging of surfaces and X-ray imaging. Key divisions within MV 2D visible light imaging are monochromatic vs. color, resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes. The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. Other 3D methods used for machine vision are a time of flight, grid-based and stereoscopic.
The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a smart camera or smart sensor. When separated, the connection may be made to specialized intermediate hardware, a frame grabber using either a standardized (Camera Link, CoaXPress) or custom interface. MV implementations also have used digital cameras capable of direct connections (without a frame grabber) to a computer via FireWire, USB or Gigabit Ethernet interfaces.
Application
The primary uses for machine vision are automatic inspection and industrial robot guidance. Common machine vision applications include quality assurance, sorting, material handling, robot guidance, and optical gauging.
1. For automatic PCB inspection.
2. For wood quality inspection
3. Final inspection of sub-assemblies
4. Engine part inspection
5. Label inspection of products
6. Checking medical devices for defects
7. Final inspection cells
8. Robot guidance and checking orientation of components
9. Packaging Inspection
10. Medical vial inspection
11. Food pack checks
12. Verifying engineered components
Methods
Machine vision methods are defined as both the process of defining and creating an MV solution and as the technical process that occurs during the operation of the solution. Here the latter is addressed. As of 2006, there was little standardization in the interfacing and configurations used in MV. This includes user interfaces, interfaces for the integration of multi-component systems and automated data interchange. Nonetheless, the first step in the MV sequence of operation is the acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing. MV software packages then employ various digital image processing techniques to extract the required information and often make decisions (such as pass/fail) based on the extracted information.
Imaging
While conventional (2D visible light) imaging is most commonly used in MV, alternatives include imaging various infrared bands, line scan imaging, 3D imaging of surfaces and X-ray imaging. Key divisions within MV 2D visible light imaging are monochromatic vs. color, resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes. The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. Other 3D methods used for machine vision are a time of flight, grid-based and stereoscopic.
The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a smart camera or smart sensor. When separated, the connection may be made to specialized intermediate hardware, a frame grabber using either a standardized (Camera Link, CoaXPress) or custom interface. MV implementations also have used digital cameras capable of direct connections (without a frame grabber) to a computer via FireWire, USB or Gigabit Ethernet interfaces.
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