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CVP Basic Exam QUESTIONS WITH Detailed Answer Key For (2025|2026) Exam, A+ Solutions

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CVP Basic Exam QUESTIONS WITH Detailed Answer Key For (2025|2026) Exam, A+ Solutions

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CVP Basic Exam QUESTIONS WITH Detailed
Answer Key For (2025|2026) Exam, A+ Solutions

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Terms in this set (49)


It is the automatic acquisition and analysis of images
What is Machine Vision? to obtain desired data for controlling or evaluating a
specific part or activity

- Automated AND Non‐Contact
- Acquisition AND Analysis
Definition of Machine
- Data/information delivery
Vision
- Technologies AND methods
- An engineering discipline

- Help eliminate dedicated mechanical solutions
Benefits of Using Machine - Provide flexibility in automated processes
Vision - Help to improve quality, enable related
technologies, and reduce costs

MV (as a set of methods) - A critical part of machine vision that is required in
What is Image order to achieve an image that can provide the
Acquisition? information needed in the application.

The overall process of extracting information from the
image.
What is Image Analysis?
(Machine Vision - as a set
Includes tasks like pre‐processing, feature extraction,
of methods)
object segmentation, identification, measurement and
more.

, What is Data/Results Making real‐world decisions about the information
Integration? (Information gained from the image. The link to the automation
gained from the image....) process

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
"Machine Vision" or
video and continuous process
"Computer Vision"
(definition, differences)
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 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" vs
Machine vision is not necessarily a subset of computer
"Computer Vision"
vision and computer vision is not necessarily a subset
(definition continued)
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

Check presence/absence, detect defects, verify
MV Definition - "Inspect"
assembly, differentiate colors, count objects

Find randomly oriented features or object is 2D and
MV Definition -
3D space, perhaps provide real-world coordinates for
"Locate/Guide"
robotic or motion guidance

Precisely measure objects or features in both 2D and
MV Definition - "Measure"
3D space.
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