Machine vision (MV) is the technology and techniques utilized to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be looked at distinct from computer vision, a type of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real-world problems. The word is the prevalent one for these functions in industrial automation environments but can also be used for these functions in other environments including security and vehicle guidance.

The overall Top Machine Vision Inspection System Manufacturer includes planning the details in the requirements and project, and then making a solution. During run-time, the procedure starts off with imaging, then automated analysis of the image and extraction of the required information.

Definitions of the term “Machine vision” vary, but all are the technology and methods used to extract information from a picture upon an automated basis, instead of image processing, in which the output is yet another image. The information extracted can be considered a simple good-part/bad-part signal, or even more a complex set of information like the identity, position and orientation of every object in an image. The data can be utilized for such applications as automatic inspection and robot and process guidance in industry, for security monitoring and vehicle guidance. This field encompasses a huge number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is virtually the only real saying used for such functions in industrial automation applications; the phrase is less universal for these functions in other environments like security and vehicle guidance. Machine vision as being a systems engineering discipline can be considered distinct from computer vision, a kind of basic computer science; machine vision efforts to integrate existing technologies in new ways and apply these to solve real-world problems in a way that meets the requirements of industrial automation and other application areas. The phrase can also be used in a broader sense by trade events and trade groups such as the Automated Imaging Association as well as the European Machine Vision Association. This broader definition also encompasses products and applications most often related to image processing. The key uses of machine vision are automatic inspection and industrial robot/process guidance. See glossary of machine vision.

Imaging based automatic inspection and sorting

The key uses for machine vision are imaging-based automatic inspection and sorting and robot guidance.;:6-10 within this section the former is abbreviated as “automatic inspection”. The overall process includes planning the facts of the requirements and project, and after that developing a solution. This section describes the technical method that occurs during the operation in the solution.

Methods and sequence of operation

Step one within the automatic inspection sequence of operation is acquisition of your image, typically using cameras, lenses, and lighting that has been designed to supply the differentiation essental to subsequent processing. MV software packages and programs created in them then employ various digital image processing methods to extract the desired information, and often make decisions (like pass/fail) based on the extracted information.


The ingredients of an automatic inspection system usually include lighting, a camera or some other imager, a processor, software, and output devices.3


The imaging device (e.g. camera) can either be apart from the primary image processing unit or along with it in which case the mixture is generally known as a smart camera or smart sensor When separated, the bond may be produced to specialized intermediate hardware, a custom processing appliance, or perhaps a frame grabber within a computer using either an analog or standardized digital interface (Camera Link, CoaXPress) MV implementations also employ cameras able to direct connections (without having a framegrabber) to some computer via FireWire, USB or Gigabit Ethernet interfaces.

While conventional (2D visible light) imaging is most commonly used in MV, alternatives include multispectral imaging, hyperspectral imaging, imaging various infrared bands,line scan imaging, 3D imaging of surfaces and X-ray imaging. Key differentiations within MV 2D visible light imaging are monochromatic vs. color, frame rate, resolution, and whether the imaging process is simultaneous over the entire image, rendering it ideal for moving processes.

Though the vast majority of machine vision applications are solved using two-dimensional imaging, Automated Vision Inspection Machines utilizing 3D imaging really are a growing niche within the industry. The most frequently used way of 3D imaging is scanning based triangulation which utilizes motion from the product or image during the imaging process. A laser is projected on the surfaces nefqnm an object and viewed from a different angle. In machine vision this can be accomplished using a scanning motion, either by moving the workpiece, or by moving the camera & laser imaging system. The line is viewed by a camera coming from a different angle; the deviation from the line represents shape variations. Lines from multiple scans are assembled in to a depth map or point cloud. Stereoscopic vision is utilized in special cases involving unique features present in both views of a pair of cameras. Other 3D methods used for machine vision are period of flight and grid based.One strategy is grid array based systems using pseudorandom structured light system as used by the Microsoft Kinect system circa 2012.

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