These are Deep Learning For Computer Vision Week 2 Nptel Answers. All weeks of Deep Learning For Computer Vision Nptel available here.
Table of Contents
Deep Learning For Computer Vision Week 2 Nptel Answers
Deep Learning For Computer Vision Week 2 Nptel Answers (July-Dec 2025)
Question 1.Given below are 4 statements. (1) The retina takes spatial and temporal derivatives. (2) If we multiply the LoG filter matrix to itself and convolve an input image with it across patches, it is equivalent to computing the square of the Laplacian at each such patch. (3) Image segmentation involves grouping similar images and segregating dissimilar images from a given set of images. (4) Fourier transform involves storing both magnitude and phase. Identify the correct set of statements from above. a) 1, 4 b) 1, 2, 4 c) 1, 2, 3 d) 2, 4
Question 2.Match the following: a) 1 → iii, 2 → iv, 3 → i, 4 → ii b) 1 → iii, 2 → i, 3 → ii, 4 → v c) 1 → iii, 2 → iv, 3 → v, 4 → ii d) 1 → iv, 2 → iii, 3 → i, 4 → ii
Question 4.In terms of computational efficiency, how does the separability of a 2D convolution kernel affect the filtering process? a) It has no effect on efficiency b) It allows the convolution to be performed as two 1D convolutions, which is faster c) It requires more memory but fewer computations d) None of the above
Question 5.Which of the following operations is an example of linear filtering? a) Thresholding an image b) Histogram equalization c) Morphological dilation d) Applying a Gaussian blur
Question 6.What is the purpose of creating a scale space in SIFT? a) To remove noise from the image b) To detect features at different scales c) To enhance edge detection d) To compress the image
Question 7.Choose the correct statements from among the following: For any low-pass or high-pass filter, the sum of the filter coefficients always adds up to 1. Brightness enhancement by image addition is a point operation. k(a∗b) = (ka) ∗ (kb), where a is the image, b is the filter, k is a scalar and ∗ is the convolution operator. a) only 1 b) 1 and 2 c) only 2 d) None of the above
Question 8.Which of the following statements is false? a) Real-world RGB images can be thought of as matrices in continuous space on ℝ³, but the images we store on a computer are discrete. b) We can represent an RGB image as a function of the form f: ℝ³ → ℝ where ℝ³ represents image coordinates (channel, height, width) and ℝ represents intensity. c) The transformation Ī(x, y) = I(x, −y) flips the image I upside down. d) Denoising an image through the moving average filter is an example of global operation as opposed to point or local operations.
Question 9.Assertion (A): Gabor filters are particularly effective for texture analysis in image processing. Reason (R): Gabor filters can be tuned to respond to specific frequencies and orientations in an image. Choose the correct answer from the options below: a) Both A and R are true, and R is the correct explanation of A. b) Both A and R are true, but R is not the correct explanation of A. c) A is true, but R is false. d) A is false, but R is true
Question 10.Which property is SIFT designed to be invariant to? a) Only rotation b) Only scale c) Rotation and scale d) Scale, rotation, and illumination changes
Question 11.What is the primary difference between blob detection and corner detection? a) Blob detection finds regions, while corner detection finds points b) Blob detection finds circles, while corner detection finds rectangles c) Corner detection works on color images, while blob detection only works on gray scale d) Blob detection requires machine learning, while corner detection doesn’t
Q2. Match the following: 1) Gaussian filter i) Edges found when gradient is low 2) Sobel filter ii) Edges found at zero crossing 3) First derivative of Gaussian iii) Edge smoothing 4) Second derivative of Gaussian iv) Edge detection v) Edges found when gradient is high
These are Deep Learning For Computer Vision Week 2 Nptel Answers
Q3.Identify the correct sequence of steps in a Canny edge detection pipeline. Steps are listed below:
1.Compute gradient magnitude and direction 2. Connect individual components 3. Smoothen the image 4. Threshold into strong, weak, or no edge 5. Gaussian Filter and Hysteresis 6. Non-maximum suppression 7. Apply derivative to get edges
6 →1 →4 →5 →2
3 →1 →6 →4 →2
3 →5 →1 →4 →2
6 →8 →5 →7 →2
Answer: Updating Soon (in progress)
Q4. In terms of computational efficiency, how does the separability of a 2D convolution kernel affect the filtering process? It has no effect on efficiency It allows the convolution to be performed as two 1D convolutions, which is faster It requires more memory but fewer computations None of the above
These are Deep Learning For Computer Vision Week 2 Nptel Answers
Q5. Which of the following operations is an example of linear filtering? Thresholding an image Histogram equalization Morphological dilation Applying a Gaussian blur
Answer: Updating Soon (in progress)
Q6.What is the purpose of creating a scale space in SIFT? To remove noise from the image To detect features at different scales To enhance edge detection To compress the image
These are Deep Learning For Computer Vision Week 2 Nptel Answers
Choose the correct statements from among the following:
Q7.1.For any low-pass or high-pass filter, the sum of the filter coefficients always adds up to 1. 2.Brightness enhancement by image addition is a point operation. 3.k(a∗b)=(ka)∗(kb), where a is the image, b is the filter, k is a scalar and ∗ is the convolution operator. only 1 1 and 2 only 2 None of the above
Real-world RGB images can be thought of as matrices in continuous space on R3, but the images we store on a computer are discrete.
We can represent an RGB image as a function of the form. f:R3→R where R3 represents image coordinates (channel, height, width) and R represents intensity.
The transformation I^(x,y)=I(x,−y) flip the image I upside down. Denoising an image through the moving average filter is an example of global operation as opposed to point or local operations.
Answer: Updating Soon (in progress)
Q9.Assertion (A): Gabor filters are particularly effective for texture analysis in image processing. Reason (R): Gabor filters can be tuned to respond to specific frequencies and orientations in an image. Choose the correct answer from the options below:
Both A and R are true, and R is the correct explanation of A. Both A and R are true, but R is not the correct explanation of A. A is true, but R is false. A is false, but R is true
Answer: Updating Soon (in progress)
Q10. Which property is SIFT designed to be invariant to? Only rotation Only scale Rotation and scale Scale, rotation, and illumination changes
Answer: Updating Soon (in progress)
Q11. What is the primary difference between blob detection and corner detection? Blob detection finds regions, while corner detection finds points Blob detection finds circles, while corner detection finds rectangle Corner detection works on color images, while blob detection only works on gray scale Blob detection requires machine learning, while corner detection doesn’t
Answer: Updating Soon (in progress)
Q12.Given is a 3 × 3 image,
The central element after applying linear contrast stretching is: 54 25 13 18
Answer: Updating Soon (in progress)
These are Deep Learning For Computer Vision Week 2 Nptel Answers
All weeks of Deep Learning For Computer Vision Week 2 Nptel Answers- Check Here
For answers to additional Nptel courses, please refer to this link: Check here
