Machine Vision Basics 02 - Camera Fundamentals
Summary
TLDRThis script delves into the fundamentals of machine vision cameras, highlighting their critical components and specifications. It explains the roles of CCD and CMOS sensors, resolution in pixels, and the distinction between array burst and line scan cameras. The importance of grayscale versus color imaging, color depth, and the impact of sensor size on lens selection is underscored. Additionally, it touches on the trade-off between high resolution and processing speed, emphasizing the importance of selecting the right camera for specific machine vision applications.
Takeaways
- π· A machine vision camera captures light from an object, which is then transmitted through a lens to create a digital image on an imager.
- π The camera can utilize either a CCD or CMOS sensor to convert light into a digital image.
- ποΈβπ¨οΈ Resolution in machine vision cameras is measured by the number of pixels or the size of the imager.
- π There are two types of machine vision cameras: array burst and line scan, each serving different applications.
- π Grayscale cameras are predominant, often used over color cameras, as they represent light intensity through pixel values.
- π’ Color depth is the number of intensity levels, typically expressed in gray levels, which helps in setting thresholds for machine vision applications.
- π§ The lens is crucial for focusing light onto the imager, and its selection depends on the image sensor size.
- π Working distance is the space between the camera lens and the object being inspected, impacting the field of view.
- π Depth of field is the range within which the object remains in focus, affecting the sharpness of the image.
- π Resolution is the system's ability to distinguish closely spaced features, a critical factor for detailed inspections.
- π₯ Frame rate, measured in frames per second, indicates how fast the camera can capture images, which is essential for high-speed applications.
Q & A
What is the primary function of a machine vision camera?
-A machine vision camera captures an image of an object by transmitting light from the object through a lens, which then creates an image on the imager that converts the light into a digital image.
What are the two types of sensors that can be found inside a machine vision camera?
-The two types of sensors found inside a machine vision camera are CCD (Charge-Coupled Device) and CMOS (Complementary Metal-Oxide-Semiconductor).
How can the resolution of a machine vision camera be measured?
-The resolution of a machine vision camera can be measured either by the number of pixels or by the size of the imager.
What are the two main types of machine vision cameras mentioned in the script?
-The two main types of machine vision cameras are area scan cameras, which create two-dimensional images with a matrix of pixels, and line scan cameras, which create a single row image with one line of pixels.
What is the difference between an area scan camera and a line scan camera?
-An area scan camera captures a two-dimensional image with a matrix of pixels, while a line scan camera captures a single row image with one line of pixels and multiple rows are acquired to create a 2D image.
Why might grayscale cameras be preferred over color cameras in machine vision applications?
-Grayscale cameras are often preferred because they can be more cost-effective and may be sufficient for the majority of applications, which typically require detecting light intensity rather than color information.
What does the term 'imager size' refer to in the context of machine vision cameras?
-Imager size refers to the physical dimensions of the image sensor in a machine vision camera, which affects the camera's field of view and the lens selection.
What is the relationship between pixel size and the depth of field in a machine vision camera?
-Pixel size affects the depth of field; smaller pixel sizes can result in a shallower depth of field, meaning the range over which the image will be sharp is narrower.
How is color depth defined in machine vision cameras?
-Color depth is defined by the number of intensities or shades of gray that can be detected by each image pixel, and it is expressed in gray levels.
What is the trade-off between image resolution and processing speed in machine vision cameras?
-Higher image resolution provides more detail but can reduce processing speed, including a lower frame rate, especially in high-speed applications where a lower resolution camera might be used.
How does the frame rate of a machine vision camera affect its application?
-The frame rate, which is the frequency at which the imager produces unique images, affects the camera's suitability for high-speed applications; a higher frame rate allows for faster image capture.
Outlines
π· Basics of Machine Vision Cameras
This paragraph introduces the fundamental concepts of machine vision cameras. It explains how light from an object is captured by the camera and transformed into a digital image through a lens and imager. Key terms such as CCD and CMOS sensors, resolution in pixels, grayscale and color cameras, imager size, pixel size, lens, working distance, field of view, depth of field, and resolution are discussed. The differences between area scan and line scan cameras are highlighted, with area scan cameras producing a two-dimensional image through a matrix of pixels and line scan cameras creating a single row image that is combined to form a 2D image. The paragraph also touches on the importance of grayscale and color depth in machine vision applications.
π Understanding Camera Specifications
This paragraph delves deeper into the specifications of machine vision cameras, focusing on the types of sensors (CCD or CMOS), resolution measured in pixels, and the distinction between array burst and line scan cameras. It also discusses the importance of grayscale images where each pixel represents light intensity information, and color depth, which is the number of intensities detected by the camera. The impact of color depth on the shades of gray and how it is represented in machine vision software is explained, with an example of how black and white are represented by the values 0 and 255, respectively. The paragraph further explains the relationship between image sensor size, resolution, frame rate, and the need to select the appropriate lens based on the sensor size for optimal performance.
Mindmap
Keywords
π‘Machine Vision
π‘CCD Sensor
π‘CMOS Sensor
π‘Resolution
π‘Array Camera
π‘Line Scan Camera
π‘Grayscale Camera
π‘Color Camera
π‘Color Depth
π‘Lens
π‘Field of View
π‘Depth of Field
π‘Frame Rate
Highlights
A machine vision camera captures light from an object, which is then transmitted through a lens to create a digital image on an imager.
There are two types of sensors in machine vision cameras: CCD and CMOS.
Resolution in machine vision is determined by the number of pixels or the size of the imager.
Machine vision cameras are categorized as either area scan or line scan cameras based on their image creation method.
An area scan camera produces a two-dimensional image with a matrix of pixels, while a line scan camera creates a single row image.
Grayscale cameras are more commonly used, accounting for over 90% of applications, due to their light intensity information.
Color depth in machine vision refers to the number of intensities detected by each image pixel, expressed in gray levels.
The value range for grayscale in machine vision is from 0 (black) to 255 (white), with various shades in between.
Selecting the correct lens is crucial and depends on the image sensor size to ensure proper image capture.
Image resolution is directly related to the amount of detail in an image, with higher resolutions providing more detail.
Higher image resolutions may result in a loss of processing speed, affecting the frame rate of the camera.
Frame rate is the frequency at which the imager produces images, measured in frames per second.
For high-speed applications, a lower resolution camera is often used to maintain fast image processing.
The lens is an optical device that projects the imaging area onto the imager, affecting the field of view.
Depth of field is the range over which the image will be sharp, determined by the lens and object distance.
Working distance is the distance between the camera lens and the object being inspected.
Machine vision applications often require setting thresholds based on the grayscale values of the objects being inspected.
Transcripts
here's an image of a machine vision
camera when you're taking a picture of
an object with the camera the light
comes from the object its transmitted
through a lens creating an image on the
imager this imager converts the light
into a digital image let's go over some
of the optical system fundamentals of
what goes into a machine vision camera
and also some of the machine vision
camera terms camera specifications you
can have a CCD or a CMOS sensor inside
of a machine vision camera your
resolution that also we can go by number
of pixels you have two different types
of machine vision cameras you have an
array burst a line scan you can have a
grayscale or a color camera imager size
and pixel size a lens is the optical
device to protect an object into the
imager working distance is the distance
between the object that you're
inspecting and your camera lens field of
view is the imaging area that's
projected onto the imager by the lens
depth of field the range of the lens to
the object distance over which the image
will be sharp and then the resolution is
the ability of an optical system to
distinguish two features that are close
together and we'll get into more of
these details as we go along an area
scan camera versus a line scan camera an
area scan camera it's an imager that
creates two-dimensional image as it has
a matrix of pixels in a line scan camera
this imager creates a single row image
as it only has one line of pixels create
a workable image multiple rows are
acquired and connected to each other
creating a 2d image now each of these
machine vision cameras have their own
unique set of machine vision
applications and that's why there
we have two different types of machine
vision cameras probably over 90% of our
applications are solve grayscale cameras
it could be even higher than that so a
grayscale image the value of each pixel
represents the light intensity
information color depth identifies the
number of intensities on the example
shades of gray are based on the number
of bits of the ad conversation it's
going to be detected by every image
pixel color depth is expressed in gray
levels so in the impact software that is
data logics machine vision software you
can tell on this chart that su 0 would
be completely black and 255 is supposed
to be completely white but I think with
this PowerPoint template it kind of has
a shade of gray to it but 255 is
supposed to be completely white so black
is 0
and white is 255 and the gray the dark
and light Gray's in between each have
their own numbers and this is helpful
when solving machine vision applications
setting thresholds and a lot about how
we get our numbers from the objects that
we are inspecting so an image sensor
comes in different sizes different
resolutions and frame rates depending on
the imager size you have to select the
correct lens to fit the sensor each lens
is designed for a specific imager size
and it can also be used in smaller
sensors just for example 2/3 can be used
on a third of an imager and there you
have a image sensor sizing chart in your
top right hand corner image resolution
refers to the amounts of pixels in an
image er a higher resolution means more
image to details for example the higher
you take a TV your TV for example the
higher you go up in resolution the
better picture you're gonna have but we
in higher resolution comes you will lose
processing speed so for example frame
rate is the
frequency at which the imager produces
how fast it can produce these unique
images is called in frames per second so
in most cases on the higher resolution
the slower the framerate is going to be
so for extremely high speed applications
a lower resolution camera is typically
used
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