Machine Vision system (the eye of the machine)
How does Machine Vision work?
Software and hardware combined work to make MV systems possible. The purpose of all its capabilities is to grant machines the power of vision aiming to imitate human sight. But devices need to go through the process of acquiring, analysing and understanding images.
Machines learn from millions of uploaded images, thanks to the interactive-learning process made possible through neural networks, which uses pattern recognition to distinguish many different sections of an image. MV starts with info to help the machine learn a specific topic; the goal is to identify the object and its attributes.
Businesses use MV systems to improve quality, efficiency and operations. The significant number of images from digital cameras on our mobiles includes photos, videos, photographs from motion detectors, data from thermal or infrared sensors, and other sources; images shared online are billions, so, MV makes data manageable and affordable, and more truthful than humans’, as it acts quickly in response to visual inputs.
MV do this through the use of several components as a) computer software able of analysing images; b) digital or analogue cameras; c) lighting suitable for cameras to take quality images; d) sensors; e) frame-grabber; f) algorithms to recognise patterns.
These components work together when using MV to inspect products in the manufacturing process. The digital-frame grabber converts the camera image into digital outputs and then protects them in a computer to analyse it by means of the software system. This software contrasts the file against a series of pre-arranged criteria to pinpoint defects. If it spots an imperfection, the product will go under required-inspection.
How is Machine Vision used in business?
MV is used for quality control purposes, helping businesses in many ways for identification, inspection, guidance; for instance, in:
- Inventory control and management: MV is core to the process of reading barcodes and labels on components, for the bin-picking carried out by robots in warehouses, for inventory control in the manufacturing process, and to move down an assembly line.
- Industrial tasks: MV relies on the digital sensors embedded in industrial cameras with specialised optics to get images, so that computer hardware/software can process, analyse, and measure their various characteristics for decision making.
- Product tracking and traceability: MV facilitates heavily-regulated industries such as the pharmaceutical, to track ingredients, product serial numbers, and monitor expiration dates.
- Correcting production line defects: it finds out where difficulties appeared in a production line, so to take remedial action to solve them.
- Farming: MV finds out the location of fruits or vegetables so that robotic harvesting machines can pick bunches without spoiling the product. It can monitor crops and detect diseases on plants.
- Safety: MV improves safety efficiency at a construction site where there could be heavy equipment or tracking supplies.
- Quantitative measurement: MV outdoes the analysis of a structured scene because of its speed, accuracy, and repeatability, quickly inspects thousands of parts per minute in detail, too tiny for the human eye to detect.
- MV helps to avoid product damage, reduces maintenance time and costs caused by mechanical issues. It brings additional safety-operational benefits when diminishing human participation in manufacturing processes, as it inhibits the contamination of cleanrooms whilst protecting workers from hazardous environments.
- MV parts location-tools must involve intelligence to quickly and accurately contrast training patterns to real objects moving down a production line and to achieve reliable results.
Summing up: MV is for sure a piece of our lives, as you might install it often even without realising where or when. Recognising the greatness in the human eye would help you to understand the efficiency of Computer Vision.
Is your business supported by Machine Vision?
Dave Food