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Digital Image Processing Multiple Choice Questions | MCQs | Quiz

Digital Image Processing Interview Questions and Answers
Pratice Digital Image Processing questions and answers for interviews, campus placements, online tests, aptitude tests, quizzes and competitive exams.

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•   Digital Image Processing
•   Image Processing Steps
•   Image Sampling Basics
•   Digital Images
•   Image Quantization
•   Image Sensing
•   Electromagnetic Spectrum
•   Mathematical Tools
•   Smoothing Spatial Filters
•   Transformation Functions
•   Sharpening Spatial Filters-1
•   Sharpening Spatial Filters-2
•   Sharpening Spatial Filters-3
•   Spatial Enhancements
•   Spatial Filtering Basics
•   Histogram Processing - 1
•   Histogram Processing - 2
•   Smoothing Spacial Filters
•   Smoothing Linear Filters
•   Smoothing Nonlinear Filter
•   Spatial Filtering
•   Frequency Domain Filtering
•   Smoothing Domain Filters
•   Emphasis Filtering
•   Homomorphic Filtering
•   Intensity Functions
•   Fuzzy Techniques
•   Piecewise Linear Functions
•   Gaussain Lowpass Filters
•   Visual Perception Elements
•   Pixels Relationships
•   Color Fundamentals
•   Color Models
•   Regional Descriptors
•   Boundary Descriptors
•   Grey Level Resolutions
•   Zooming & Shrinking
•   Image Enhancement Basics
•   Grey Level Transformation
•   Histogram Equalization
•   Histogram Specification
•   Logic Operations
•   Arithmetic Operations
•   Second Order Derivatives
•   First Order Enhancement
•   Laplacian Frequency

Best Reference Books

Digital Image Processing Books

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Digital Image Processing Questions and Answers – Fundamentals of Spatial Filtering

Posted on June 27, 2017 by Manish

This set of Digital Image Processing Multiple Choice Questions & Answers (MCQs) focuses on “Fundamentals of Spatial Filtering”.

1. What is accepting or rejecting certain frequency components called as?
a) Filtering
b) Eliminating
c) Slicing
d) None of the Mentioned
View Answer

Answer: a
Explanation: Filtering is the process of accepting or rejecting certain frequency components.

2. A filter that passes low frequencies is _____________
a) Band pass filter
b) High pass filter
c) Low pass filter
d) None of the Mentioned
View Answer

Answer: c
Explanation: Low pass filter passes low frequencies.

3. What is the process of moving a filter mask over the image and computing the sum of products at each location called as?
a) Convolution
b) Correlation
c) Linear spatial filtering
d) Non linear spatial filtering
View Answer

Answer: b
Explanation: The process is called as Correlation.

4. The standard deviation controls ___________ of the bell (2-D Gaussian function of bell shape).
a) Size
b) Curve
c) Tightness
d) None of the Mentioned
View Answer

Answer: c
Explanation: The standard deviation controls “tightness” of the bell.

5. What is required to generate an M X N linear spatial filter?
a) MN mask coefficients
b) M+N coordinates
c) MN spatial coefficients
d) None of the Mentioned
View Answer

Answer: a
Explanation: To generate an M X N linear spatial filter MN mask coefficients must be specified.

6. What is the difference between Convolution and Correlation?
a) Image is pre-rotated by 180 degree for Correlation
b) Image is pre-rotated by 180 degree for Convolution
c) Image is pre-rotated by 90 degree for Correlation
d) Image is pre-rotated by 90 degree for Convolution
View Answer

Answer: b
Explanation: Convolution is the same as Correlation except that the image must be rotated by 180 degrees initially.

7. Convolution and Correlation are functions of _____________
a) Distance
b) Time
c) Intensity
d) Displacement
View Answer

Answer: d
Explanation: Convolution and Correlation are functions of displacement.

8. The function that contains a single 1 with the rest being 0s is called ______________
a) Identity function
b) Inverse function
c) Discrete unit impulse
d) None of the Mentioned
View Answer

Answer: c
Explanation: It is called Discrete unit impulse.

9. Which of the following involves Correlation?
a) Matching
b) Key-points
c) Blobs
d) None of the Mentioned.
View Answer

Answer: a
Explanation: Correlation is applied in finding matches.

10. An example of a continuous function of two variables is __________
b) Intensity function
c) Contrast stretching
d) Gaussian function
View Answer

Answer: d
Explanation: Gaussian function has two variables and is an exponential continuous function.

Sanfoundry Global Education & Learning Series – Digital Image Processing.

To practice all areas of Digital Image Processing, here is complete set of 1000+ Multiple Choice Questions and Answers.

« Prev Page - Digital Image Processing Questions and Answers – Combining Spatial Enhancements Methods
» Next Page - Digital Image Processing Questions And Answers – Histogram Processing – 2
« Digital Image Processing Questions and Answers – Combining Spatial Enhancements Methods
Digital Image Processing Questions And Answers – Histogram Processing – 2 »

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