# NPTEL Deep Learning for Computer Vision week 2 Assignment Answers 2024

## NPTEL Deep Learning for Computer Vision week 2 Assignment Answers 2024

1. Which of the following are examples of a high-pass filter? (Select all possible correct options)

2.

• 1 →iii, 2 →iv, 3 →i, 4 →ii
• 1 →iii, 2 →i, 3 →ii, 4 →v
• 1 →iii, 2 →iv, 3 →v, 4 →ii
• 1 →iv, 2 →iii, 3 →i, 4 →ii

3. 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

4. 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

5. Which of the following operations is an example of linear filtering?

• Thresholding an image
• Histogram equalization
• Morphological dilation
• Applying a Gaussian blur

6. 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

7. Choose the correct statements from among the following:

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

8. Which of the following statements is false?

• 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.

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:

• 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

10. Which property is SIFT designed to be invariant to?

• Only rotation
• Only scale
• Rotation and scale
• Scale, rotation, and illumination changes

11. 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