CVP Basic Exam complete with
verified solutions(latest updated
version already graded A+)
What is Machine Vision? - answer It is the automatic
acquisition and analysis of images to obtain desired data
for controlling or evaluating a specific part or activity
Definition of Machine Vision - answer - Automated AND
Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision - answer - Help eliminate
dedicated mechanical solutions
- Provide flexibility in automated processes
- Help to improve quality, enable related technologies, and
reduce costs
MV (as a set of methods) - What is Image Acquisition? -
answer 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? (Machine Vision - as a set of
methods) - answer 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? (Information gained
from the image....) - answer Making real‐world decisions
about the information gained from the image. The link to
the automation process
"Machine Vision" or "Computer Vision" (definition,
differences) - answer Computer vision most commonly
refers to the use of AI techniques for classification of
objects (e.g. neural networks and deep learning) to make
computers "see" in a perceptive way that mimics humans;
streaming video and continuous process
Machine vision most commonly refers to the use of
discrete feature extraction and rule‐based comparisons to
make decisions directly on image data, 1‐1 relationship
part to process
"Machine Vision" vs "Computer Vision" (definition
continued) - answer 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
verified solutions(latest updated
version already graded A+)
What is Machine Vision? - answer It is the automatic
acquisition and analysis of images to obtain desired data
for controlling or evaluating a specific part or activity
Definition of Machine Vision - answer - Automated AND
Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision - answer - Help eliminate
dedicated mechanical solutions
- Provide flexibility in automated processes
- Help to improve quality, enable related technologies, and
reduce costs
MV (as a set of methods) - What is Image Acquisition? -
answer 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? (Machine Vision - as a set of
methods) - answer 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? (Information gained
from the image....) - answer Making real‐world decisions
about the information gained from the image. The link to
the automation process
"Machine Vision" or "Computer Vision" (definition,
differences) - answer Computer vision most commonly
refers to the use of AI techniques for classification of
objects (e.g. neural networks and deep learning) to make
computers "see" in a perceptive way that mimics humans;
streaming video and continuous process
Machine vision most commonly refers to the use of
discrete feature extraction and rule‐based comparisons to
make decisions directly on image data, 1‐1 relationship
part to process
"Machine Vision" vs "Computer Vision" (definition
continued) - answer 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
