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CVP Basic Exam: Study Guide & Practice Test Questions

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Prepare for the CVP Basic Exam with our comprehensive study guide. Includes practice questions, detailed answers, and key concepts for Certified Venous Physician certification.

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age 1 of 20




CVP BASIC EXAM 2025/2026 COMPLETE QUESTIONS

WITH CORRECT DETAILED ANSWERS || 100%

GUARANTEED PASS <BRAND NEW VERSION>

What is Machine Vision? .......Answer.........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 .......Answer.........- Automated AND

Non‐Contact


- Acquisition AND Analysis


- Data/information delivery


- Technologies AND methods


- An engineering discipline

,age 2 of 20




Benefits of Using Machine Vision .......Answer.........- 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?

.......Answer.........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)

.......Answer.........The overall process of extracting information

from the image.

, age 3 of 20




Includes tasks like pre‐processing, feature extraction, object

segmentation, identification, measurement and more.


What is Data/Results Integration? (Information gained from the

image....) .......Answer.........Making real‐world decisions about the

information gained from the image. The link to the automation

process


"Machine Vision" or "Computer Vision" (definition, differences)

.......Answer.........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
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