View A Video on Machine Vision - A Quick Introduction
Machine vision processes can be undertaken by modular devices such as smart cameras or fully integrated machine vision systems such as those that might be present in robotic vision applications involving AGV. Though they perform many other tasks, quality control is one of the largest embodiments of machine vision as optical inspection systems, vision inspection systems and even laser inspection allow manufactures to assess products at higher-speed, consistency, repeatability and magnification, far exceeding the work period and capabilities of a human workforce. Vision sensors in conjunction with vision software emulate human sight by capturing images and then interpreting the collected data. With these interpretations optical sorting systems aid in the continued flow of production as products can be quickly sorted based on shape, size, material or any other pre-determined aspect. Though highly sophisticated, some limitations do exist as machine vision is not adaptable to the same degree as human processing. machine vision products nevertheless continue to grow in popularity and functionality as they consistently improve the productivity, reliability and quality of manufacturing across the industrial sector.
As aforementioned, machine vision systems can perform a large number of variable tasks and as such are incorporated in an equally extensive array of industries. Automotive and electronic fields are among the most visible applications as AGV equipment is commonly employed in the inspection and construction of components. This and other industries use machine vision to inspect not only the final product, but the components used to build them as well. Tool and die, casting and molding components are frequently inspected under high magnification to reduce the risk of running full production with inaccurate parts. Often multiple aspects of machine vision are employed as with pharmaceutical packaging where both counting and inspection is performed to ensure the proper filling of vital prescription medications. Human safety is one of the leading reasons for employing machine vision. In addition to medical applications, recycling and waste management facilities frequently employ machine vision technology to promote workforce safety when potentially dangerous or contaminated materials need sorting. The sensors are often required in the performance of tasks as well. Labeling machines, for example, commonly use smart vision technology to determine when a product is in proper position for application. Food processing, counterfeit identification, textile, pulp and paper and airport baggage sorting list just a handful of the many additional industrial applications for machine vision systems. Not all smart cameras or vision software are applied to industry, however, as one of the most common applications, for example is the facial recognition feature available in many handheld digital cameras.
The many industrial applications for machine vision coupled with the use of this technology in both commercial and residential sectors inherently necessitates a broad range of devices available for matrix matching, feature extraction or general purpose visibility applications. While machine vision products vary considerably, vision systems often employ the same basic components. These include vision sensors, digital camera or image capture device, lighting, computer processor and special image processing software. Often placed at a given point along a conveyor belt, machine vision begins with sensors that detect when a product or component is in position. This triggers the camera or imaging device and lighting which are often synchronized to produce a digital image which highlights features of interest. A digitizing device known as a frame grabber then converts the camera output and enters the data into the memory of the computer system. Vision software processes the image using several steps such as the removal of static within the image and mathematical algorithms to count, measure, identify or inspect the object. The interpretation of the given data is compared to predetermined criteria programmed by the developer. A simplified user interface then allows workers to view the progress and success rate of production.
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. In addition to the specific system configuration, there are several operational specifications that should be considered in order to ensure the optimal use of machine vision in a given application. Inspection rate and product speed are both important factors and should be compatible to ensure that every part or object undergoes standard evaluation. The number of cameras and processor speed as well as data storage capacities are also variable and should be considered with a specific use in mind. Test samples or vision calibration targets are commonly used in order achieve the proper parameters for pre-programmed machine vision systems and smart cameras in order to avoid the possibility of distortion. Using such a prototype is especially useful in inspection systems as it can create the computerized model with exact surface and material features. Despite the many advantages apparent over human vision, machine vision is inherently limited. Even with nearly continual advancements of both hardware and software pertaining to this highly skilled field, computer vision programs lack the ability to adapt beyond pre-determined algorithms as human vision so aptly does. Machine vision works best when performing narrowly defined tasks, though continued advancements continually improve the performance possibilities of this technology.
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Machine Vision Types
- are
cameras that use CCD (charge coupled device) chips to convert
photons
to electrical or digital information. Instead of the image
being recorded
on film, the CCD image is placed in an image file on the
computer.
- Computer vision is an amalgamation of computer science, optics, mechanical engineering and industrial automation aimed at the mechanized extrapolation of the information present in visual images.
- Laser inspection involves the use of a specific type of photoelectric sensor that employs a highly focused beam of light to detect surface defects at a microscopic level, count parts as they move through production and scan codes or serial numbers as needed for a given application.
-
is often used to create 3-D images of a recorded surface.
Lasers produce
high powered light with electrical properties.
- Machine vision products
- Machine vision systems mimic human vision in machinery.
-
uses the magnetic properties of material to create a visual
slice or
image via an x-ray type sensor.
- Optical inspection systems ensure quality by inspecting products with machine vision.
- Optical sorting systems use machine vision to accurately sort
products.
- Robotic vision is the practical application of computer vision providing semi-autonomous machines and devices with a limited visual capacity as needed in industrial and manufacturing settings.
- Smart
Cameras have image processing circuitry and software within them.
While smart
cameras are highly mobile, they lack large storage capacity,
and so
are often connected to a central computer to alleviate this
problem.
- Vision inspection systems use machine vision in assembly lines to search for surface defects,
count products, and scan serial numbers, among other things.
- Vision sensors are integral to the field of machine vision as they allow for the capture of precision imagery and the subsequent analysis of the information present in that image.
- Vision software is the computer or processor programming that extrapolates and extracts information from imagery and converts it into usable data.
- Vision systems
Machine Vision Terms
-
A technology that provides 3D images from a large quantity of 2D
cross-sectional
images. These images are assembled in a computer from pictures
or scans
taken of a desired piece.
- The
manner in
which outside information is brought into an analysis system.
- The
diameter of the
lens, which controls the amount of light that reaches the
photoconductive
image sensor.
-
Reduction of signal
strength.
- Quality of
color, which
includes both hue and saturation.
- The
restoration
of original information from compressed data.
-
The range of
the distance from the sensor to the object at which the lens is
focused.
-
Conversion
of a video picture into pixels by means of an A/D converter,
where the
level of each pixel can be stored in a computer.
- A
filter used
to transmit light based on wavelength rather than on the plane
of vibration.
Dichroic filters will transmit one color while reflecting a
second, when
illuminated with white light.
-
Light source
or optical image delivery via long, flexible fibers of
transparent material,
usually bundled together. Light is transmitted via internal
reflection
inside each fiber; coherent fiber optics are spatially organized
so images
can be relayed.
- The
plane perpendicular
to the lens axis at the point of focus, usually found at the
image sensor.
- The
amount of frames
that are displayed per unit of time.
- The
non-contact dimensional
examination of an object.
-
Variations of values
from white through shades of gray to black in a digitized image
with black
assigned the value of zero and white the value of one.
- An
incandescent
lamp inside which is a gas similar to iodine that is constantly
evaporated
and then redeposited on the filament.
-
The process
of identifying objects and shapes in a photograph, drawing,
video or other
visual image. Image analysis is used for everything from
colorizing classic
motion pictures to piloting cruise missiles.
- The
plane surface
of the imaging sensor, perpendicular to the viewing direction,
at which
the optics are focused.
- The
region of the
electromagnetic spectrum adjacent to the visible spectrum, just
beyond
red with longer wavelengths.
- Classification
of images into predetermined categories, usually using
statistical methods.
- Acronym for
picture
element. Pixels are the individual elements in a digitized image
array.
-
The process
of manufacturing at both the design and production stage.
Process imaging
is a generic term for quality control imaging.
- An
image processing
operation that enhances edges. A non-sharp mask adds a low-pass,
filtered
image to the original, resulting in edge enhancement.
- An
electrical or mechanical
device used to control the amount of time the imaging surface is
exposed
to light. The shutter is often used to stop the blur created by
moving
objects.
-
Enhancing
an image by changing its spatial frequencies.
- A
compound lens
that remains in focus as the image size is continuously varied. A
zoom
lens may be motorized or manually operated.
