Machine Vision Applications Courtesey of Matrox
- A quest for the best—looking fruits and vegetables, that is!
- Smart camera helps the wheels go 'round and 'round
- Machine vision helps port terminals increase productivity
- Inspecting turbine blades in aircraft engines
- Vision automates parking surveillance
- Vision helps delta robot sort biscuits
A quest for the best—looking fruits and vegetables, that is!
Matrox Imaging Library (MIL) ensures that only the highest quality produce reaches grocery store shelves
(courtesy Matrox Imaging)
It is estimated that more than 30 per cent of fruits and vegetables grown for North American consumers are discarded before they reach grocery store shelves because of "cosmetic imperfections". An apple is too small, a pear is the wrong color or a cucumber is misshapen. Imperfect produce that does manage to reach supermarkets remains unsold for the most part and ultimately ends up in landfill sites. In this era of skyrocketing food costs and global shortages it is in everyone's best interests—growers, packers, distributors, retailers, and consumers—to reduce this waste.
The vision system includes proprietary double sensor CMOS high-resolution cameras (one color and one infrared camera per lane), acquisition boards, and LED lighting. Twenty color pictures and 20 infrared pictures are taken of each piece of fruit as it moves and rotates forward—covering 100 % of its surface. The vision system can perform optical sizing (equatorial or maximum diameter, volume integration), color sorting (eight different criteria), and detection of external defects on the fruit.
The images are then processed using the Matrox Imaging Library (MIL) toolkit. Binarization and blob analysis are used to separate the fruit from its background and to obtain dimensions like Feret diameters and elongation, for example. The HLS (Hue, Luminosity, Saturation) color space conversion and statistical functions are used for color processing. And convolutions and custom-designed algorithms recognize stems and cores, and reject fruit with defects on the skin like black spots or russet.
Smart camera helps the wheels go 'round and 'round
Machine vision-based assembly system fits and mounts wheels onto cars in continuous operation
(courtesy Matrox Imaging)
Smart camera-based image processing
The image processing system is based upon the Matrox Iris GT smart camera. The application was developed with Matrox Design Assistant, an integrated development environment (IDE) that is bundled with the camera. The IDE lets users create machine vision applications by constructing a flowchart instead of coding programs or scripts using languages like C++. Once development is finished, the project (or flowchart) is uploaded and stored locally on the Matrox Iris GT. The project is then executed on the smart camera and monitored from the web-based Human Machine Interface (HMI) running on a PC.
A number of Design Assistant tools or flowchart steps are used. Image acquisition and processing are triggered by a command from the network link, which contains information about the measurement job and the expected rim type. Several Model Finder steps are used to locate the wheel’s bolt circle and to verify the expected type of design. The Metrology step then calculates the rim’s position and orientation based on data provided by the Model Finder occurrences. A TCP/IP connection ensures communication between the smart cameras and the PLC. Results and images are logged to a shared network folder—using TextWriter and ImageWriter steps—and can be downloaded by remote maintenance staff for fault analysis.
Machine vision helps port terminals increase productivity - Ship-to-shore container cranes rely upon Matrox Imaging smart cameras for safe and efficient shipping of cargo
(courtesy Matrox Imaging)
Machine vision’s role in anti-sway systems
MicroView & LingZhi Image Tech Corporation (MVLZ) (Beijing, China) has developed an automated ship-to-shore anti-sway system that incorporates machine vision. The port’s bridge crane includes a machine vision system, a fiber optic communication link, Programmable Logic Controller (PLC)-based feedback control system, and an electronic control system.
The machine vision system is based upon a Matrox Iris smart camera. In addition to the smart camera, the system includes a 12 mm lens with a near infrared (NIR) pass filter, custom NIR lights, and cabling.
The Matrox Iris smart camera is mounted on the trolley, while the light sources on the spreader are used as markers. The camera grabs images of the markers continuously and calculates the center point of two markers in real time. This information is transmitted over an RS-232 link, itself converted to a fiber optic link (and then back to an RS-232 link) to reliably cover the long distance between the smart camera and PLC. The location of the center point is continuously provided to the PLC. The PLC gives commands to the electronic control system, which regulates trolley movement so that container sway is reduced.
Inspecting turbine blades in aircraft engines
(courtesy Matrox Imaging)
Turbines that are housed in aircraft engines are subjected to pretty tough conditions. They must perform at speeds of 30 thousand rpm in temperatures greater than 800ºC for hours at a time.
The engine manufacturers fully understand that even small surface defects can reduce performance, increase maintenance costs, and reduce the useful life of an aircraft engine. They need to inspect turbine blades very carefully to maintain the efficiency and reliability that the air transport industry requires.
One particular North American manufacturer inspected its blades by hand and human eye. The highly-trained inspectors measured hundreds of features and checked for surface defects at depths in the order of thousandths of an inch. Manual inspection was not only costly in terms of time and labour, but subjective as well. Results were variable and even differed between inspectors. Finally, because manual inspection was so time consuming, there was no systematic inspection of every blade; only a sampling of blades was inspected. The manufacturer required an approach that would allow systematic inspections of the blades, save time, and yield consistent and repeatable results.
Vision automates parking surveillance
(courtesy Matrox Imaging)
Instead of looking on parking fees and fines as a ‘cash cow’, some enlightened cities attempt to balance their needs with those of business owners and residents. Fredericksburg, VA is one city that revolutionized the way it manages parking. By adopting an automated parking system using a vehicle mounted vision system, the city has enjoyed greater revenues, improved efficiency, and far fewer complaints and repeat offenders.
Vision helps delta robot sort biscuits
(courtesy Matrox Imaging)
A major European cookie and chocolate maker outputs 30 million packages a year, and they contain over 80 different types of assorted cookies. This manufacturer needed a solution that could support the wide variety of products and a high throughput.
The Astor line of robots was the perfect candidate. The Astor features a vision-guided delta robot that can pick and place 140 units per minute. In this cookie packaging installation, there are eight robot cells on the plant floor that collectively sort 1 120 cookies per minute. Each cell sorts one or two cookie varieties for the package. As the blister tray passes each work cell, the robot stacks three or four cookies in the appropriate section of the blister tray.
