Published by: sadikshya
Published date: 27 Jun 2021
This is the question set of Computer Graphics and Image Processing 2017, which was taken by the Pokhara University.
Pokhara University – Computer Graphics and Image Processing 2017
| Level: Bachelor | Semester –sixth | Year: 2017-Fall |
| Program: BCIS | Full Marks: 100 | |
| Course: Computer Graphics and Image Processing | Pass Marks: 45 | |
| Time: 3hrs. | ||
Section “A”
Very Short Answer Questions
Attempt all the questions.
1. Define digital image processing.
2. What are the different types of Neighborhoods of pixels?
3. What are four different application areas of Digital Image Processing?
4. Write filter matrix for Prewitt and Sobel filters.
5. What are probability density functions for Gaussian and Exponential noise?
6. Define Dilation and Erosion operation.
7. Write down steps for image enhancement in the frequency domain.
8. Define lossless and lossy compression.
9. Define Neural Network.
10. Define pattern and pattern class.
Section “B”
Descriptive Answer Questions
Attempt any six questions
11. What do you mean by histogram and normalized histogram? Derive equalized histogram for following histogram of an Image.
12. Write down expressions for 1-D and 2-D forward and inverse DCT. Calculate transform matrix for Haar Transform for 4-points.
13. What do you mean by inter-pixel redundancy? Explain run length coding
14. Define Opening and Closing Operation. Discuss the use of this operation. Write down their properties.
15. What do you mean by segmentation? Explain threshold-based segmentation methods.
16. Explain different color models.
17. Describe chain code and signatures for object representation.
18. Section”C”
Case Analysis
a) Apply 3×3 Uniform Averaging and Weightage Averaging Filter in the following image for bold pixels.
10 70 60 20 20
40 60 20 30 30
10 5 30 30 30
20 20 50 25 30
20 20 50 25 20
b) While capturing an Image, the Image is distorted by periodic noise from nearby electrical equipment. You are assigned to design a technique to eliminate that noise. Explain what will be the technique you will use to restore the image.