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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.

Applications.
The primary uses for machine vision are automatic inspection and industrial robot guidance. Other machine vision applications include:
• Automated Train Examiner (ATEx) Systems
• Automatic PCB inspection
• Wood quality inspection
• Final inspection of sub-assemblies
• Engine part inspection
• Label inspection on products
• Checking medical devices for defects
• Final inspection cells
• Robot guidance and checking orientation of components
• Packaging Inspection
• Medical vial inspection
• Food pack checks
• Verifying engineered components.
• Wafer Dicing
• Reading of Serial Numbers
• Inspection of Saw Blades
• Inspection of Ball Grid Arrays (BGAs)
• Surface Inspection
• Measuring of Spark Plugs
• Molding Flash Detection
• Inspection of Punched Sheets
• 3D Plane Reconstruction with Stereo
• Pose Verification of Resistors
• Classification of Non-Woven Fabrics.
Methods.
Machine vision methods are defined as both the process of defining and creating an MV solutionand 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 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.