CVP Basic Exam
Questions Grade A+
What is Machine Vision? - ANSWERSIt 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 - ANSWERS- Automated AND Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision - ANSWERS- 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? - ANSWERSA 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) - ANSWERSThe 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....) - ANSWERSMaking
real‐world decisions about the information gained from the image. The link to the automation
process
"Machine Vision" or "Computer Vision" (definition, differences) - ANSWERSComputer 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) - ANSWERSMachine 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" - ANSWERSCheck presence/absence, detect defects, verify assembly,
differentiate colors, count objects
MV Definition - "Locate/Guide" - ANSWERSFind randomly oriented features or object is 2D and
3D space, perhaps provide real-world coordinates for robotic or motion guidance
MV Definition - "Measure" - ANSWERSPrecisely measure objects or features in both 2D and 3D
space.
Questions Grade A+
What is Machine Vision? - ANSWERSIt 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 - ANSWERS- Automated AND Non‐Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
Benefits of Using Machine Vision - ANSWERS- 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? - ANSWERSA 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) - ANSWERSThe 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....) - ANSWERSMaking
real‐world decisions about the information gained from the image. The link to the automation
process
"Machine Vision" or "Computer Vision" (definition, differences) - ANSWERSComputer 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) - ANSWERSMachine 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" - ANSWERSCheck presence/absence, detect defects, verify assembly,
differentiate colors, count objects
MV Definition - "Locate/Guide" - ANSWERSFind randomly oriented features or object is 2D and
3D space, perhaps provide real-world coordinates for robotic or motion guidance
MV Definition - "Measure" - ANSWERSPrecisely measure objects or features in both 2D and 3D
space.
