The term machine vision (MV) refers to the technology and methods used by engineers to mimic human vision. Machine vision systems allow them to access image-based automatic inspection, recognition, and analysis of different parts in production. In addition, machine vision systems facilitate the precise and accurate performance of tasks, like defect recognition, sorting, guidance, and bar code scanning, without any product damage.
Individual machine systems are often quite different from one another, as they serve diverse applications, but generally speaking, they all work using the same basic components. These components are vision sensors, lighting, an image capture device or digital camera, a computer processor, and special image processing software. Read More…
The most common way that vision sensors are used is in a scanning-based triangulation method wherein vision sensors activate the first step of vision sensing, the acquisition of an image, by detecting the presence and position of a product or component. When the vision sensor recognizes that the product or component is in place, the imaging device or camera is triggered, along with the lighting, with which it is frequently synchronized. This synchronous action produces a digital image that illuminates features of interest.
The imaging device can be combined with the computer processor or it may be separate. If connected, the combined unit is called a smart sensor or smart camera. If not, a specialized intermediate hardware device, called a frame grabber, is used to collect and convert the imaging device’s output and enter it as date into the computer system. After this, the machine vision image processing software steps in.
The many steps of processing include: stitching/registration, filtering, thresholding, pixel counting, segmentation, inpainting, edge detection, color analysis, blob discovery and manipulation, neutral net processing, pattern recognition, optical character recognition, barcode, 2D barcode and Data Matrix reading, gauging/metrology, and comparison against target values to determine a “pass or fail” “go/no go” result. The ultimate goal of vision software is to count, measure, identify, or inspect the object and compare it to the criteria set by the object’s developer. Along with this, workers can use a simplified interface that allows them to check the progress and success rate of production.
Different machine vision systems focus on certain tasks. One of the most widespread tasks that they undertake is that of quality control. Quality control can mean a lot of things, and in the context of machine vision, a few things it often refers to are the overseeing of proper sorting of goods on a production line and inspection of goods and parts. Vision inspection systems, optical inspection systems, and laser inspection systems are among the machine vision systems used to assess products based on shape, size, material, or any other programmed factor, with consistency, speed, repetition, and magnification.
They also help with the fast and accurate filling and packaging of prescription medications, other pharmaceutical goods and pulp and paper. In terms of inspecting products for quality, two of the biggest fields that employ machine vision systems are the electronic and automotive industries. In these industries, manufacturers make especially great usage out of AGV (automated guided vehicle) equipment to inspect their products.
As well as inspecting finished products, these industries and more, such as the industrial manufacturing industry, use machine vision systems to inspect the parts used to make them. Such parts and components include die casts, molds, and tools, which are routinely inspected under high magnification.
Another focus of machine vision systems is human safety and security. Areas in which machine vision contributes to this include recycling and waste management facilities, where machine vision technology spares the workforce from having to sort contaminated or dangerous materials, at the airport, where it helps scan and sort baggage and at stores and banks, where it can detect counterfeit bills. In addition, machine vision systems help with performance tasks like labeling, food processing, textile machining, and facial recognition.
Thanks to machine vision, images and processes in the industrial, residential, and commercial worlds alike continue to become more accessible and more accurate. To create the best systems possible, system designers carefully consider application requirements and more. Application requirements and specifications will determine system camera quantity, data storage capacity, and processor speed.
In addition, for optimal performance, engineers take care to make sure that the product speed and inspection rate of a system are compatible with one another. To avoid the possibility of distortion by establishing the proper program parameters, they will also commonly use calibration targets or take test samples. They may also use a prototype to create a computerized model of an inspection system, complete with exact material and surface features.
With this basic order of events and necessary components in mind, engineers often develop application specific custom machine vision systems and products for industrial, commercial, and residential applications.