CVP BASIC EXAM Question and Answer
(2026/2027) | Complete Revision Guide |
A+ Verified
• What is Machine Vision? -✓✓ 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 -✓✓ - 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
• MV (as a set of methods) - What is Image Acquisition? -✓✓ 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) -✓✓ 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....) -✓✓
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 (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) -✓✓ 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
(2026/2027) | Complete Revision Guide |
A+ Verified
• What is Machine Vision? -✓✓ 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 -✓✓ - 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
• MV (as a set of methods) - What is Image Acquisition? -✓✓ 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) -✓✓ 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....) -✓✓
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 (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) -✓✓ 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
