CVP BASIC EXAM QUESTIONS AND ANSWERS
What is Machine Vision? - Answers - 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 - 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? - Answers - 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) - Answers - 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....) - Answers -
Making real‐world decisions about the information gained from the image. The link to
the automation process
"Machine Vision" or "Computer Vision" (definition, differences) - Answers - 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) - Answers - 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" - Answers - Check presence/absence, detect defects, verify
assembly, differentiate colors, count objects
MV Definition - "Locate/Guide" - Answers - Find randomly oriented features or object is
2D and 3D space, perhaps provide real-world coordinates for robotic or motion
guidance
MV Definition - "Measure" - Answers - Precisely measure objects or features in both 2D
and 3D space.
MV Definition - "Identify/Sort" - Answers - Differentiate closely related objects or
features, read codes and print, sort/count objects based on size, color or other features.
What is the Key to Success (understanding MV Market & Industry) [goal of CVP] -
Answers - Being able to competently specify and implement the technology
True/False - Industrial PC or Embedded PC Based Systems include "Smart Cameras" -
Answers - False
ASMV - Answers - Application Specific Machine Vision
Fundamental Machine Vision Process Tasks: in order (no system architecture deviates
from this) - Answers - acquisition‐>analysis‐>data and results
At the most basic level all systems use the same constituent building blocks: (what are
they?) - Answers - optics/illumination‐>imaging device‐>computing device/software
What are the typical characteristics of:
general purpose machine vision - external computer or "PC‐based"
& similar system architectures? - Answers - High flexibility and scalability in both
imaging devices and computing power, often general purpose libraries and operating
systems
"Centralized" processing
What are the typical characteristics of:
smart cameras
What is Machine Vision? - Answers - 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 - 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? - Answers - 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) - Answers - 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....) - Answers -
Making real‐world decisions about the information gained from the image. The link to
the automation process
"Machine Vision" or "Computer Vision" (definition, differences) - Answers - 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) - Answers - 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" - Answers - Check presence/absence, detect defects, verify
assembly, differentiate colors, count objects
MV Definition - "Locate/Guide" - Answers - Find randomly oriented features or object is
2D and 3D space, perhaps provide real-world coordinates for robotic or motion
guidance
MV Definition - "Measure" - Answers - Precisely measure objects or features in both 2D
and 3D space.
MV Definition - "Identify/Sort" - Answers - Differentiate closely related objects or
features, read codes and print, sort/count objects based on size, color or other features.
What is the Key to Success (understanding MV Market & Industry) [goal of CVP] -
Answers - Being able to competently specify and implement the technology
True/False - Industrial PC or Embedded PC Based Systems include "Smart Cameras" -
Answers - False
ASMV - Answers - Application Specific Machine Vision
Fundamental Machine Vision Process Tasks: in order (no system architecture deviates
from this) - Answers - acquisition‐>analysis‐>data and results
At the most basic level all systems use the same constituent building blocks: (what are
they?) - Answers - optics/illumination‐>imaging device‐>computing device/software
What are the typical characteristics of:
general purpose machine vision - external computer or "PC‐based"
& similar system architectures? - Answers - High flexibility and scalability in both
imaging devices and computing power, often general purpose libraries and operating
systems
"Centralized" processing
What are the typical characteristics of:
smart cameras
