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, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as being a systems engineering discipline can be regarded as distinct from computer vision, a type of computer science. It tries 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 can also be used for these functions in other environments like security and vehicle guidance.
The general Top Machine Vision Inspection System Manufacturer includes planning the specifics of the requirements and project, and then developing a solution. During run-time, the process starts with imaging, accompanied by automated analysis of the image and extraction in the required information.
Definitions of the term “Machine vision” vary, but all are the technology and methods used to extract information from a graphic with an automated basis, rather than image processing, in which the output is an additional image. The information extracted can be a simple good-part/bad-part signal, or more a complicated set of information such as the identity, position and orientation of each object inside an image. The information can be applied for such applications as automatic inspection and robot and process guidance in industry, for security monitoring and vehicle guidance. This field encompasses a lot of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is virtually the sole saying used for these particular functions in industrial automation applications; the word is less universal for these particular functions in other environments such as security and vehicle guidance. Machine vision as a systems engineering discipline can be considered 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 in which meets the prerequisites of industrial automation and other application areas. The term is also used in a broader sense by industry events and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications generally connected with image processing. The key uses for machine vision are automatic inspection and industrial robot/process guidance. See glossary of machine vision.
Imaging based automatic inspection and sorting
The primary uses of 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 general process includes planning the specifics in the requirements and project, and after that making a solution. This section describes the technical method that occurs throughout the operation of the solution.
Methods and sequence of operation
The initial step within the automatic inspection sequence of operation is acquisition of the image, typically using cameras, lenses, and lighting which has been made to supply the differentiation necessary for subsequent processing. MV software applications and programs developed in them then employ various digital image processing techniques to extract the desired information, and often make decisions (like pass/fail) based on the extracted information.
The ingredients of the 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 coupled with it where case the mixture is generally referred to as a smart camera or smart sensor When separated, the link 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 cameras able to direct connections (without having a framegrabber) to your computer via FireWire, USB or Gigabit Ethernet interfaces.
While conventional (2D visible light) imaging is most commonly 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 if the imaging process is simultaneous on the entire image, which makes it suitable 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 throughout the imaging process. A laser is projected to 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 your 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 into 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 duration of flight and grid based.One strategy is grid array based systems using pseudorandom structured light system as utilized by the Microsoft Kinect system circa 2012.