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

The general Top Machine Vision Inspection System Manufacturer includes planning the facts from the requirements and project, and after that making a solution. During run-time, this process starts off with imaging, accompanied by automated analysis of the image and extraction of the required information.

Definitions of the term “Machine vision” vary, but all include the technology and techniques employed to extract information from an image upon an automated basis, instead of image processing, in which the output is yet another image. The data extracted can become a simple good-part/bad-part signal, or more a complex set of data such as the identity, position and orientation of each object in an image. The details can be used for such applications as automatic inspection and robot and process guidance in industry, for security monitoring and vehicle guidance. This industry encompasses a huge number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is actually the only expression used for such functions in industrial automation applications; the word is less universal for these functions in other environments like security and vehicle guidance. Machine vision as a systems engineering discipline can be regarded as distinct from computer vision, a type of basic computer science; machine vision attempts to integrate existing technologies in new ways and apply those to solve real life problems in a way that meets the prerequisites of industrial automation and similar application areas. The word is also used in a broader sense by trade events and trade groups like the Automated Imaging Association as well as the European Machine Vision Association. This broader definition also encompasses products and applications generally related to image processing. The key ways to use machine vision are automatic inspection and industrial robot/process guidance. See glossary of machine vision.

Imaging based automatic inspection and sorting

The key ways to use machine vision are imaging-based automatic inspection and sorting and robot guidance.;:6-10 in this section the former is abbreviated as “automatic inspection”. The overall process includes planning the facts of the requirements and project, and then making a solution. This section describes the technical procedure that occurs throughout the operation of the solution.

Methods and sequence of operation

The initial step inside the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting that has been created to supply the differentiation essental to subsequent processing. MV software packages and programs created in them then employ various digital image processing strategies to extract the required information, and often make decisions (including pass/fail) based on the extracted information.


The constituents of your automatic inspection system usually include lighting, a camera or any other imager, a processor, software, and output devices.3


The imaging device (e.g. camera) can either be apart from the main image processing unit or combined with it where case the combination is generally referred to as a smart camera or smart sensor When separated, the connection may be produced to specialized intermediate hardware, a custom processing appliance, or even a frame grabber within a computer using either an analog or standardized digital interface (Camera Link, CoaXPress) MV implementations also employ digital 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 often found 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, making it ideal for moving processes.

Though the majority of machine vision applications are solved using two-dimensional imaging, Automated Vision Inspection Machines utilizing 3D imaging certainly are a growing niche within the industry. Probably the most commonly 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 to the surfaces nefqnm an object and viewed from a different angle. In machine vision this really is accomplished using a scanning motion, either by moving the workpiece, or by moving the digital camera & laser imaging system. The line is viewed with a camera coming from a different angle; the deviation from the line represents shape variations. Lines from multiple scans are assembled right into a depth map or point cloud. Stereoscopic vision is utilized in special cases involving unique features present in both views of a set of cameras. Other 3D methods employed for machine vision are time of flight and grid based.One method is grid array based systems using pseudorandom structured light system as utilized by the Microsoft Kinect system circa 2012.

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