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 describes many technologies, hardware and software products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be regarded as distinct from computer vision, a form of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real life problems. The phrase 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 specifics of the requirements and project, and then making a solution. During run-time, the procedure starts with imaging, followed by automated research into the image and extraction in the required information.
Definitions of the term “Machine vision” vary, but all are the technology and techniques employed to extract information from a picture on an automated basis, rather than image processing, in which the output is another image. The information extracted can become a simple good-part/bad-part signal, or maybe more a complex set of data including the identity, position and orientation of every object within 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 industry encompasses a huge number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is actually the only real saying used for these functions in industrial automation applications; the term is less universal for these functions in other environments such as security and vehicle guidance. Machine vision as a systems engineering discipline can be looked at distinct from computer vision, a form of basic computer science; machine vision tries to integrate existing technologies in new ways and apply these to solve real-world problems in a way that meets the prerequisites of industrial automation and other application areas. The phrase can also be used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications generally associated with image processing. The primary 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 within this section the former is abbreviated as “automatic inspection”. The overall process includes planning the facts from the requirements and project, and then developing a solution. This section describes the technical process that occurs during the operation in the solution.
Methods and sequence of operation
The initial step within the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting which has been made to supply the differentiation required by subsequent processing. MV software packages and programs created in them then employ various digital image processing techniques to extract the desired information, and frequently make decisions (including pass/fail) based on the extracted information.
The components of your 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 outside of the key image processing unit or along with it where case a combination is normally called 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 have digital camera models capable of direct connections (with no framegrabber) to some 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 whether or not the imaging process is simultaneous over 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 are a growing niche within the industry. The most frequently used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image throughout the imaging process. A laser is projected on the surfaces nefqnm an object and viewed from a different angle. In machine vision this really is accomplished having 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 a different angle; the deviation in the line represents shape variations. Lines from multiple scans are assembled into a depth map or point cloud. Stereoscopic vision can be used in special cases involving unique features present in both views of a pair of cameras. Other 3D methods employed for machine vision are time 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.