M.Tech AI & ML Computer Vision Exam 2026/2027–
Practice Questions & Answers with Rationales
SECTION A — COMPUTER VISION FUNDAMENTALS
1. What is the primary goal of computer vision?
A. Store images efficiently
B. Enable machines to interpret and reason about visual information
C. Increase processor clock speed
D. Compress all images
Answer: B
Rationale: Computer vision focuses on extracting meaningful
information from images and video so machines can perceive and
reason about the visual world.
2. A digital image can be represented mathematically as:
A. A one-dimensional text sequence only
B. A two-dimensional function of spatial coordinates and intensity
C. A database table only
D. A collection of audio samples
Answer: B
Rationale: A grayscale image can be modeled as f(x,y), where x and y
specify spatial position and f represents intensity.
3. In a grayscale image, a pixel primarily represents:
A. A color spectrum only
B. An intensity value
C. A camera model
D. A feature descriptor
,Answer: B
Rationale: Each grayscale pixel contains an intensity measurement,
commonly represented using 8 bits.
4. An 8-bit grayscale image can represent how many intensity levels?
A. 8
B. 128
C. 256
D. 512
Answer: C
Rationale: Eight bits provide 2⁸ = 256 possible values, typically 0
through 255.
5. RGB images contain three channels corresponding to:
A. Red, green, and blue
B. Radius, gradient, and brightness
C. Range, geometry, and brightness
D. Red, grayscale, and binary
Answer: A
Rationale: RGB represents color using red, green, and blue intensity
channels.
6. What does image resolution primarily describe?
A. The number of pixels used to represent an image
B. The image's compression algorithm
C. The camera's battery capacity
D. The number of objects detected
Answer: A
Rationale: Resolution commonly refers to the spatial dimensions or
number of pixels representing an image.
,7. Spatial resolution is mainly associated with:
A. Number of color channels
B. Pixel density and spatial detail
C. Image file extension
D. Compression ratio
Answer: B
Rationale: Higher spatial resolution generally permits representation of
finer spatial details.
8. Quantization in image processing refers to:
A. Sampling spatial coordinates
B. Mapping continuous intensity values to discrete levels
C. Detecting edges
D. Removing objects
Answer: B
Rationale: Quantization discretizes amplitude or intensity values.
9. Sampling primarily determines:
A. Spatial discretization
B. Color temperature
C. Object class labels
D. Network bandwidth
Answer: A
Rationale: Sampling converts continuous spatial coordinates into
discrete pixel locations.
10. The Nyquist principle states that the sampling frequency should
be:
A. Less than the highest signal frequency
B. Equal to zero
, C. At least twice the highest frequency component
D. Independent of signal frequency
Answer: C
Rationale: Sampling at least twice the highest frequency is required to
avoid aliasing under ideal conditions.
11. Aliasing occurs when:
A. An image contains too many channels
B. Sampling is insufficient to capture spatial frequencies
C. An image is perfectly reconstructed
D. Pixels are all identical
Answer: B
Rationale: Undersampling causes high-frequency content to appear as
misleading lower-frequency patterns.
12. Which color space separates brightness from chromatic
information?
A. RGB
B. HSV
C. Binary
D. CMYK only
Answer: B
Rationale: HSV separates hue and saturation from value, making it
useful for some color-based vision tasks.
13. In HSV, hue primarily represents:
A. Brightness
B. Color type
C. Image resolution
D. Noise level
Practice Questions & Answers with Rationales
SECTION A — COMPUTER VISION FUNDAMENTALS
1. What is the primary goal of computer vision?
A. Store images efficiently
B. Enable machines to interpret and reason about visual information
C. Increase processor clock speed
D. Compress all images
Answer: B
Rationale: Computer vision focuses on extracting meaningful
information from images and video so machines can perceive and
reason about the visual world.
2. A digital image can be represented mathematically as:
A. A one-dimensional text sequence only
B. A two-dimensional function of spatial coordinates and intensity
C. A database table only
D. A collection of audio samples
Answer: B
Rationale: A grayscale image can be modeled as f(x,y), where x and y
specify spatial position and f represents intensity.
3. In a grayscale image, a pixel primarily represents:
A. A color spectrum only
B. An intensity value
C. A camera model
D. A feature descriptor
,Answer: B
Rationale: Each grayscale pixel contains an intensity measurement,
commonly represented using 8 bits.
4. An 8-bit grayscale image can represent how many intensity levels?
A. 8
B. 128
C. 256
D. 512
Answer: C
Rationale: Eight bits provide 2⁸ = 256 possible values, typically 0
through 255.
5. RGB images contain three channels corresponding to:
A. Red, green, and blue
B. Radius, gradient, and brightness
C. Range, geometry, and brightness
D. Red, grayscale, and binary
Answer: A
Rationale: RGB represents color using red, green, and blue intensity
channels.
6. What does image resolution primarily describe?
A. The number of pixels used to represent an image
B. The image's compression algorithm
C. The camera's battery capacity
D. The number of objects detected
Answer: A
Rationale: Resolution commonly refers to the spatial dimensions or
number of pixels representing an image.
,7. Spatial resolution is mainly associated with:
A. Number of color channels
B. Pixel density and spatial detail
C. Image file extension
D. Compression ratio
Answer: B
Rationale: Higher spatial resolution generally permits representation of
finer spatial details.
8. Quantization in image processing refers to:
A. Sampling spatial coordinates
B. Mapping continuous intensity values to discrete levels
C. Detecting edges
D. Removing objects
Answer: B
Rationale: Quantization discretizes amplitude or intensity values.
9. Sampling primarily determines:
A. Spatial discretization
B. Color temperature
C. Object class labels
D. Network bandwidth
Answer: A
Rationale: Sampling converts continuous spatial coordinates into
discrete pixel locations.
10. The Nyquist principle states that the sampling frequency should
be:
A. Less than the highest signal frequency
B. Equal to zero
, C. At least twice the highest frequency component
D. Independent of signal frequency
Answer: C
Rationale: Sampling at least twice the highest frequency is required to
avoid aliasing under ideal conditions.
11. Aliasing occurs when:
A. An image contains too many channels
B. Sampling is insufficient to capture spatial frequencies
C. An image is perfectly reconstructed
D. Pixels are all identical
Answer: B
Rationale: Undersampling causes high-frequency content to appear as
misleading lower-frequency patterns.
12. Which color space separates brightness from chromatic
information?
A. RGB
B. HSV
C. Binary
D. CMYK only
Answer: B
Rationale: HSV separates hue and saturation from value, making it
useful for some color-based vision tasks.
13. In HSV, hue primarily represents:
A. Brightness
B. Color type
C. Image resolution
D. Noise level
