Machine vision

Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise.

The information extracted can be 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.

[1][2][3] This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise.

The first step in the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing.

[14] The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices.

[17] When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a frame grabber within a computer using either an analog or standardized digital interface (Camera Link, CoaXPress).

[18][19][20][21] MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via FireWire, USB or Gigabit Ethernet interfaces.

[27] Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras.

Machine vision image processing methods include; A common output from automatic inspection systems is pass/fail decisions.

[6] Additionally, output types include numerical measurement data, data read from codes and characters, counts and classification of objects, displays of the process or results, stored images, alarms from automated space monitoring MV systems, and process control signals.

[42] The term deep learning has variable meanings, most of which can be applied to techniques used in machine vision for over 20 years.

[43] The system learns from a large amount of images during a training phase and then executes the inspection during run-time use which is called "inference".