Vision plays a fundamental role for living beings by allowing them to interact with the environment in an effective and efficient way. Where human vision is best for qualitative interpretation of a complex, unstructured scene, machine vision excels at quantitative measurement of a structured scene because of its speed, accuracy, and repeatability. For example, on a production line, a machine vision system can inspect hundreds, or even thousands, of parts per minute. A machine vision system built around the right camera resolution and optics can easily inspect object details too small to be seen by the human eye.
What is Machine Vision?
Machine vision (also called “industrial vision” or “vision systems”) is the use of digital sensors (wrapped in cameras with specialized optics) that are connected to processing hardware and software algorithms to visually inspect pretty much anything. Machine vision is a true multi-disciplinary field, encompassing computer science, optics, mechanical engineering, and industrial automation. While historically the tools of machine vision were focused on manufacturing, that’s quickly changing, spreading into medical applications, research, and even movie making.
Machine vision is the technology to replace or complement manual inspections and measurements with digital cameras and image processing. The technology is used in a variety of different industries to automate the production, increase production speed and yield, and to improve product quality.
Machine vision in operation can be described by a four-step flow:
- Imaging: Take an image.
- Processing and analysis: Analyze the image to obtain a result.
- Communication: Send the result to the system in control of the process.
- Action: Take action depending on the vision system’s result.
Figure 1: Machine Vision Operations
Machine-Vision System Components
Machine vision allows you to obtain useful information about physical objects by automating analysis of digital images of those objects. This is one of the most challenging applications of computer technology. There are two general reasons for this: almost all vision tasks require at least some judgment on the part of the machine, and the amount of time allotted for completing the task usually is severely limited. While computers are astonishingly good at elaborate, high-speed calculation, they still are very primitive when it comes to judgment.
A machine-vision system has five key components.
Just as a professional photographer uses lighting to control the appearance of subjects, so the user of machine vision must consider the color, direction, and shape of an illumination. For objects moving at high speed, a strobe often can be used to freeze the action.
For many years, the standard machine-vision camera has been monochromatic. It outputs many shades of gray but not color, provides about 640 × 480 pixels, produces 30 frames per second, uses CCD solid-state sensor technology, and generates an analog video signal defined by television standards.
- Frame Grabber
A frame grabber interfaces the camera to the computer that is used to analyze the images. One common form for a frame grabber is a plug-in card for a PC.
Often an ordinary PC is used, but sometimes a device designed specifically for image analysis is preferred. The computer uses the frame grabber to capture images and specialized software to analyze them and is responsible for communicating results to automation equipment and interfacing with human operators for setup, monitoring, and control.
The key to successful machine-vision performance is the software that runs on the computer and analyzes the images. Software is the only component that cannot be considered a commodity and often is a vendor’s most important intellectual property.
Machine Vision Goals
Machine vision goals can be divided into following from a technical point of view:
|Strategic Goal||Machine Vision Applications|
|Higher quality||Inspection, measurement, gauging, and assembly verification|
|Increased productivity||Repetitive tasks formerly done manually are now done by Machine Vision System|
|Production flexibility||Measurement and gauging / Robot guidance / Prior operation verification|
|Less machine downtime and reduced setup time||Changeovers programmed in advance|
|More complete information and tighter process control||Manual tasks can now provide computer data feedback|
|Lower capital equipment costs||Adding vision to a machine improves its performance, avoids obsolescence|
|Lower production costs||One vision system vs. many people / Detection of flaws early in the process|
|Scrap rate reduction||Inspection, measurement, and gauging|
|Inventory control||Optical Character Recognition and identification|
|Reduced floor space||Vision system vs. operator|
 “Machine Vision Introduction”, Version 2.2, December 2006, SICK IVP, available online at: www.sickivp.com
 Bill Silver, Cognex, “An Introduction to Machine Vision a Tutorial”, available online at: https://www.evaluationengineering.com/an-introduction-to-machine-vision-a-tutorial
 “Introduction to Machine Vision: A guide to automating process & quality improvements”, available online at: www.cognex.com
 David Phillips, “Machine vision: a survey”, Western CEDAR, 2008.