CVP Basic Exam FINAL test
questions with verified
solutions
What is Machine Vision?
Machine vision is the substitution of the human
visual sense and judgment capabilities with a
camera and computer to perform an inspection
task. It is the automatic acquisition and analysis
of images to obtain desired data for controlling
or evaluating a specific part or activity.
Machine Vision-Important Points
- Automated AND Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision
- Help eliminate dedicated mechanical solutions
- Provide flexibility in automated processes
- Help to improve quality, enable related technologies, and
reduce costs
What is Image Acquisition?
It is a critical part of machine vision that is required in
order to achieve an image that can provide the
information needed in the application.
What is Image Analysis?
The overall process of extracting information from the
image.
, Includes tasks like pre‐processing, feature extraction,
object segmentation, identification, measurement and
more.
What is Data/Results Integration?
Making real‐world decisions about the information gained
from the image. The link to the automation process
"Machine Vision" or "Computer Vision" (definition,
differences)
Computer vision most commonly refers to the use of AI
techniques for classification of objects to make computers
"see" in a perceptive way that mimics humans; streaming
video and continuous process.
Machine vision uses a wide variety of tools including those
that are most often considered exclusive to "computer
vision" (deep learning for example) along with rule‐based
or discrete feature extraction and analysis
Machine vision is not necessarily a subset of computer
vision and computer vision is not necessarily a subset of
machine vision
In some cases, the capability of the tools described as
rule‐based/discrete (machine vision) and learning‐based
(computer vision) overlap and either might work well for a
target application
MV Definition - "Inspect"
Check presence/absence, detect defects, verify assembly,
differentiate colors, count objects
MV Definition - "Locate/Guide"
Find randomly oriented features or object is 2D and 3D
space, perhaps provide real-world coordinates for robotic
or motion guidance
MV Definition - "Measure"
questions with verified
solutions
What is Machine Vision?
Machine vision is the substitution of the human
visual sense and judgment capabilities with a
camera and computer to perform an inspection
task. It is the automatic acquisition and analysis
of images to obtain desired data for controlling
or evaluating a specific part or activity.
Machine Vision-Important Points
- Automated AND Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision
- Help eliminate dedicated mechanical solutions
- Provide flexibility in automated processes
- Help to improve quality, enable related technologies, and
reduce costs
What is Image Acquisition?
It is a critical part of machine vision that is required in
order to achieve an image that can provide the
information needed in the application.
What is Image Analysis?
The overall process of extracting information from the
image.
, Includes tasks like pre‐processing, feature extraction,
object segmentation, identification, measurement and
more.
What is Data/Results Integration?
Making real‐world decisions about the information gained
from the image. The link to the automation process
"Machine Vision" or "Computer Vision" (definition,
differences)
Computer vision most commonly refers to the use of AI
techniques for classification of objects to make computers
"see" in a perceptive way that mimics humans; streaming
video and continuous process.
Machine vision uses a wide variety of tools including those
that are most often considered exclusive to "computer
vision" (deep learning for example) along with rule‐based
or discrete feature extraction and analysis
Machine vision is not necessarily a subset of computer
vision and computer vision is not necessarily a subset of
machine vision
In some cases, the capability of the tools described as
rule‐based/discrete (machine vision) and learning‐based
(computer vision) overlap and either might work well for a
target application
MV Definition - "Inspect"
Check presence/absence, detect defects, verify assembly,
differentiate colors, count objects
MV Definition - "Locate/Guide"
Find randomly oriented features or object is 2D and 3D
space, perhaps provide real-world coordinates for robotic
or motion guidance
MV Definition - "Measure"
