Machine vision (MV) is the technology and methods 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 considered 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 word is the prevalent one for these functions in industrial automation environments but can also be used for these functions in other environments such as security and vehicle guidance.
The entire Top Machine Vision Inspection System Manufacturer includes planning the details in the requirements and project, then creating a solution. During run-time, this process starts off with imaging, then automated research into the image and extraction of the required information.
Definitions in the term “Machine vision” vary, but all are the technology and methods utilized to extract information from an image on an automated basis, instead of image processing, in which the output is yet another image. The details extracted can be considered a simple good-part/bad-part signal, or maybe more an intricate set of web data like the identity, position and orientation of every object in an image. The information can be used 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 actually the only real term used for such functions in industrial automation applications; the phrase is less universal for these particular functions in other environments like security and vehicle guidance. Machine vision being 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 them to solve real-world problems in a way in which meets certain requirements of industrial automation and similar application areas. The term is also used in a broader sense by trade events and trade groups including the Automated Imaging Association and also the European Machine Vision Association. This broader definition also encompasses products and applications most often related to image processing. The main 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 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 entire process includes planning the specifics from the requirements and project, and then making a solution. This section describes the technical method that occurs through the operation of the solution.
Methods and sequence of operation
The initial step in the automatic inspection sequence of operation is acquisition of the image, typically using cameras, lenses, and lighting that has been created to give you the differentiation necessary for subsequent processing. MV software applications and programs developed in them then employ various digital image processing methods to extract the desired information, and frequently make decisions (including pass/fail) based on the extracted information.
The ingredients of an 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 outside of the key image processing unit or combined with it where case the combination is usually 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 perhaps a frame grabber in a computer using either an analog or standardized digital interface (Camera Link, CoaXPress) MV implementations also use digital 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 often 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 if the imaging process is simultaneous on 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 are a growing niche within the industry. Probably the most frequently used method for 3D imaging is scanning based triangulation which utilizes motion of 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 is accomplished using a scanning motion, either by moving the workpiece, or by moving the digital camera & laser imaging system. The line is viewed by a camera from the 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 used in special cases involving unique features contained in both views of a set of cameras. Other 3D methods utilized for machine vision are time 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.