Machine Vision
MVC - Vision Systems Integrator
Custom vision solutions to manufacturing industry across the US.
www.MachineVC.com
Machine Vision Search
Free Technical Search Engine Search Thousands of Catalogs Today.
www.globalspec.com
EPSON: Machine Vision Industrial Robots
EPSON is a leading manufacturer of high-precision industrial robots, PC-based controls, machine vision systems and other factory automation products used in factories throughout the world.
www.robots.epson.com
Linear Encoders
Encoders/scales, DROs, length gages. Auth. distributor - Low prices.
www.pqi.net
Machine Vision
Find providers of machine vision systems in our directory.
www.business.com
Flexible Automation
Specializing in integrated machine vision & motion control solutions.
www.aeiboston.com
Vision System
Find vision system Search In Your Local Area Now.
Justclicklocal.com
Machine Vision from FSI Technologies
Machine vision inspection, solutions and engineering.
www.fsinet.com
Machine Vision Directory
Machine visions. The Industrial Hub.
www.Industrial101.com
Mail Scan Reading Product
Scan, documents, mail pieces, booklets, to insure integrity.
www.DDS-USA.com
Warning: mkdir() [function.mkdir]: Permission denied in /home/webs/affiliatelib2/CacheManager.php on line 12
Warning: mkdir() [function.mkdir]: No such file or directory in /home/webs/affiliatelib2/CacheManager.php on line 12
Warning: fopen(/home/templatecore2cache//*cluesnet.com/94/94fbcaba3b7e41c66dafa922d0dce1a290fb520e.tc2cache) [function.fopen]: failed to open stream: No such file or directory in /home/webs/affiliatelib2/CacheManager.php on line 130
Warning: fwrite(): supplied argument is not a valid stream resource in /home/webs/affiliatelib2/CacheManager.php on line 131
Warning: fclose(): supplied argument is not a valid stream resource in /home/webs/affiliatelib2/CacheManager.php on line 132
Machine vision (MV) is the application of computer vision to industry and manufacturing. Whereas computer vision is mainly focused on machine-based image processing, machine vision most often requires also digital input/output devices and computer networks to control other manufacturing equipment such as robotic arms. Machine Vision is a subfield of engineering that encompasses computer science, optics, mechanical engineering, and industrial automation. One of the most common applications of Machine Vision is the inspection of manufactured goods such as semiconductor chips, automobiles, food and pharmaceuticals. Just as human inspectors working on assembly lines visually inspect parts to judge the quality of workmanship, so machine vision systems use digital cameras, smart cameras and image processing software to perform similar inspections.
Machine vision systems are programmed to perform narrowly defined tasks such as counting objects on a conveyor, reading serial numbers, and searching for surface defects. Manufacturers favour machine vision systems for visual inspections that require high-speed, high-magnification, 24-hour operation, and/or repeatability of measurements. Frequently these tasks extend roles traditionally occupied by human beings whose degree of failure is classically high through distraction, illness and circumstance. However, humans may display finer perception over the short period and greater flexibility in classification and adaptation to new defects and quality assurance policies.
Computers do not 'see' in the same way that human beings are able to. Cameras are not equivalent to human optics and while people can rely on inference systems and assumptions, computing devices must 'see' by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features such as Pattern recognition engines. Although some machine vision algorithms have been developed to mimic human visual perception, a number of unique processing methods have been developed to process images and identify relevant image features in an effective and consistent manner. Machine vision and computer vision systems are capable of processing images consistently, but computer-based image processing systems are typically designed to perform single, repetitive tasks, and despite significant improvements in the field, no machine vision or computer vision system can yet match some capabilities of human vision in terms of image comprehension, tolerance to lighting variations and image degradation, parts' variability etc.
Components of a machine vision system A typical machine vision system will consist of several among the following components:
The sync sensor determines when a part (often moving on a Conveyor belt) is in position to be inspected. The sensor triggers the camera to take a picture of the part as it passes beneath the camera and often synchronizes a lighting pulse to freeze a sharp image. The lighting used to illuminate the part is designed to highlight features of interest and obscure or minimize the appearance of features that are not of interest (such as shadows or reflections). LED panels of suitable sizes and arrangement are often used to this purpose.
The camera's image is captured by the framegrabber. A framegrabber is a digitizing device (within a smart camera or as a separate computer card) that converts the output of the camera to digital format (typically a two dimensional array of numbers, corresponding to the luminous intensity level of the corresponding point in the field of view, called pixel) and places the image in computer storage so that it may be processed by the machine vision software.
The software will typically take several steps to process an image. Often the image is first manipulated to reduce noise or to convert many shades of gray to a simple combination of black and white (Binary image). Following the initial simplification, the software will count, measure, and/or identify objects, dimensions, defects or other features in the image. As a final step, the software passes or fails the part according to programmed criteria. If a part fails, the software may signal a mechanical device to reject the part; alternately, the system may stop the production line and warn a human worker to fix the problem that caused the failure.
Though most machine vision systems rely on black-and-white cameras, the use of colour cameras is becoming more common. It is also increasingly common for Machine Vision systems to include digital camera equipment for direct connection rather than a camera and separate framegrabber, thus reducing signal degradation.
Smart camera with built-in embedded processors are capturing an increasing share of the machine vision market. The use of an embedded (and often very optimized) processor eliminates the need for a framegrabber card and external computer, thus reducing cost and complexity of the system while providing dedicated processing power to each camera. Smart cameras are typically less expensive than systems comprising a camera and a board and/or external computer, while the increasing power of embedded processors and DSPs is often providing comparable or higher performance and capabilities than conventional PC-based systems.
Processing methods Commercial and open source machine vision software packages typically include a number of different image processing techniques such as the following:
- Pixel counting: counts the number of light or dark pixels
- Thresholding: converts an image with gray tones to simply black and white
- Segmentation: used to locate and/or count parts
- blob extraction : inspecting an image for discrete blobs of connected pixels (e.g. a black hole in a grey object) as image landmarks. These blobs frequently represent optical targets for machining, robotic capture, or manufacturing failure.
- Recognition-by-components: extracting Geon (psychology) from visual input
- Robust pattern recognition: location of an object that may be rotated, partially hidden by another object, or varying in size
- Barcode reading: decoding of 1D and 2D codes designed to be read or scanned by machines
- Optical character recognition: automated reading of text such as serial numbers
- Gauging: measurement of object dimensions in inches or millimeters
- Edge detection: finding object edges
- Template matching: finding, matching, and/or counting specific patterns
In most cases, a machine vision system will use a sequential combination of these processing techniques to perform a complete inspection. E.g. A system that reads a barcode may also check a surface for scratches or tampering and measure the length and width of a machined component.
Applications of machine vision The applications of Machine Vision (MV) are diverse, covering areas of endeavour including, but not limited to:
- Large-scale industrial manufacture
- Short-run unique object manufacture
- Safety systems in industrial environments
- Inspection of pre-manufactured objects (e.g. quality control, failure investigation)
- Visual stock control and management systems (counting, barcode reading, store interfaces for digital systems)
- Control of Automated Guided Vehicles (AGVs)
- Automated monitoring of sites for security and safety
- Monitoring of agricultural production
- Quality control and refinement of food products
- Retail automation
- Consumer equipment control
- Medical imaging processes (e.g. Interventional Radiology)
- Medical remote examination and procedures
Machine vision systems are widely used in semiconductor fabrication; indeed, without machine vision, yields for computer chips would be significantly reduced. Machine vision systems inspect silicon wafers, processor chips, and subcomponents such as resistors and capacitors.
In the automotive industry, machine vision systems are used to guide industrial robots, gauge the fit of stamped metal components, and inspect the surface of the painted vehicle for defects.
Though machine vision techniques were developed for the visible spectrum, the same processing techniques may be applied to images captured using imagers sensitive to other forms of spectra such as infrared light or x-ray emissions.
Related fields Machine vision is distinct from computer vision. Computer vision extends to topics related to autonomous robotics and machine representation of human vision. Machine Vision refers to automated imaging systems including a wide range of computing disciplines aggregated to form a complete solution to visual problems and can be considered a superset composed of Computer Vision and elements such as equipment control, databasing, network systems, interfacing and machine learning.
See also
- Artificial intelligence
- Barcode
- Bin picking problem
- Computer science
- Computer vision
- Digital image processing
- Household robot
- Image processing
- Industrial robot
- Machine Vision Glossary
- Machine vision optical filters
- Morphological image processing
- Medical imaging
- Optical character recognition
- Pattern recognition
- Robotic mapping
- Smart camera
- Video Analytics
Further reading . Online PDF version
External links
- Intelligent Sensors Technical Group - Society of Manufacturing Engineers
- Vision tutorial--Learn what vision is and how it works.
- The Machine Vision Portal::Buyers Guide::Solutions::News::Informations
- Informative articles on the specifics of machine vision applications
- List of smart camera manufacturers
Machine vision: a technical guide to machine vision technology
Machine vision systems are programmed to perform narrowly defined tasks such as counting objects on a conveyor, reading serial numbers, and searching for surface defects.
Vision systems integrators - MVT - Machine Vision Technology Ltd
Vision systems integrator supporting a wide range of production industries including Pharmaceutical, automotive, electronics, food, packaging, robot guidance, printing and general ...
Machine Vision Technology - Enquiry Form
Machine Vision Technology. Please complete the form to contact us and find out if we can provide the solution to your quality and vision system issues! ... To get in touch with us ...
Microsystems and Machine Vision Lab | Sheffield Hallam University
Sheffield Hallam University: Undergraduate and postgraduate full and part-time courses, research, consultancy and services for business.
Machine Vision Unit, Edinburgh
Purpose The Machine Vision Unit researches the transformation of raw signals into a symbolic representation, whether through initial investigation, an intermediate stage ...
Machine Vision Online
USA. Non-profit trade association, dedicated to promoting the use of image capture and analysis technology. Buyers'guide. Library of case studies, technical papers and articles ...
Machine vision - Wikipedia, the free encyclopedia
Machine vision (MV System) is the application of computer vision to industry and manufacturing. Whereas computer vision is mainly focused on machine-based image processing, machine ...
Sony : Machine Vision Market : United Kingdom
Analogue Cameras. Compact size component video cameras used for industrial vision applications.
The Machine Vision Laboratory, Bristol Institute of Technology
The homepage for the Machine Vision Laboratory in the Bristol Institute of Technology ... Welcome to the UWE Machine Vision Laboratory homepage. The MVL is the core component of ...
BMVC (British Machine Vision Conference) 2007
Home Committees Programme Proceedings Tutorial Keynote Speakers Awards Contact: British Machine Vision Conference 2007 University of Warwick, UK (September 10-13, 2007)