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Know the top OpenCV interview questions and answers for freshers and experienced candidates to prepare for job interviews.

Total 36 questions Interview Questions and Answers

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Know the top OpenCV interview questions and answers for freshers and experienced candidates to prepare for job interviews.

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Intermediate / 1 to 5 years experienced level questions & answers

Ques 1

What are Erosion and Dilation in OpenCV?

In OpenCV, Erosion and Dilation are the two very common morphological image processing operations which is a procedure for modifying the geometric structure in the image.
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Ques 3

What is OpenGL?

OpenGL stands for Open Graphics Library, it is an open-source cross-platform application programming interface (API) for rendering 2D and 3D vector graphics. The API is used to interact with GPU for achieving the hardware-accelerated rendering.
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Ques 4

How many types of video filters are in OpenCV?

Different types of video filters available in OpenCV are Blurring, Smoothing, Distortion, Warp Stabilizer, alpha extract, bilateral, color matrix, chrome hold, etc.
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Ques 8

What Is Image Translation And Scaling?

Image translation means reposition the image from one co-ordinate location to another along straight line path. Whereas, Scaling refers to alter the size of the object or image (ie) a co-ordinate system is scaled by a factor.
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Ques 9

What Do You Meant By Shrinking Of Digital Images?

Shrinking may be viewed as under sampling. If an image is been shrinked by one half, we delete every row and column. To reduce possible aliasing effect, it is a good idea to blue an image slightly before shrinking it.
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Ques 10

Explain Subjective Brightness And Brightness Adaptation.

Subjective brightness means intensity as preserved by the human visual system . Brightness adaptation means the human visual system can operate only from scotopic to glare limit. It cannot operate over the range simultaneously. It performs large variation by changes in its overall intensity.


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Ques 11

How can we Increase the Quality of an Image?

– Recognition and Interpretation

Image enhancement process is purely dependent on the application where we need to use the enhanced image and the type of degradation in the image. Few solutions from my basic knowledge

– If image contain so much noises, apply filtering operations such as mean/median etc.

– If the image is looking too dark or too bright apply histogram equalization process to improve the contrast.

– If the image is blurred apply sharpening operations in the image.

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