CVP Basic Vision Exam Combined, CVP Notes, CVP Basic Exam, CVP Basic Final Exam – Questions & Answers What is Machine Vision? a definition Right Ans - Machine vision is the substitution of the human visual sense and judgment capabilities with a camera and computer to perform an inspection task. It is the automatic acquisition and analysis of images to obtain desired data for controlling or evaluating a specific part or activity.Machine Vision-Important Points Right Ans - - Automated AND Non ‐ Contact
- Acquisition AND Analysis
- Data/information delivery
- Technologies AND methods
- An engineering discipline
- Provide flexibility in automated processes
- Help to improve quality, enable related technologies, and reduce costs
Benefits of Using Machine Vision in automation Right Ans - - Help eliminate dedicated mechanical solutions
What is Image Acquisition? Right Ans - It is 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? Right Ans - 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? Right Ans - Making real world decisions ‐ about the information gained from the image. The link to the automation process "Machine Vision" or "Computer Vision" (definition, differences) Right Ans - Computer vision most commonly refers to the use of AI techniques for 1 / 3
classification of objects to make computers "see" in a perceptive way that mimics humans; streaming video and continuous 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 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" Right Ans - Check presence/absence, detect defects, verify assembly, differentiate colors, count objects MV Definition - "Locate/Guide" Right Ans - Find randomly oriented features or object is 2D and 3D space, perhaps provide real-world coordinates for robotic or motion guidance MV Definition - "Measure" Right Ans - Precisely measure objects or features in both 2D and 3D space.MV Definition - "Identify/Sort" Right Ans - 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] Right Ans - Being able to competently specify and implement the technology True/False - Industrial PC or Embedded PC Based Systems include "Smart Cameras" Right Ans - False ASMV Right Ans - Application Specific Machine Vision
Fundamental Machine Vision Process Tasks: (In order) Right Ans -
acquisition >analysis >data and results
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At the most basic level all systems use the same constituent building blocks:
(what are they?) Right Ans - optics/illumination >imaging device
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>computing device/software
What are the typical characteristics of:
general purpose machine vision - external computer or "PC based" ‐ & similar system architectures? Right Ans - 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 & similar system architectures? Right Ans - Good price/performance ratio, in general good ease of use "Distributed" processing
Machine Vision systems create an image by sensing: Right Ans - light
Light for machine vision can be: (types of light) Right Ans - visible or
nonvisible active or passive emitted or reflective What do sensors convert light into? Right Ans - electrical voltage
Nothing happens in a machine vision application without the: Right Ans -
Successful capture of a very high quality image ‐ Image quality can be defined as having the Right Ans - correct resolution for the target application with best possible feature contrast"
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