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USN AM622T3A
Sixth Semester B.E. Degree Examination MODEL QUESTION PAPER
IMAGE PROCESSING AND COMPUTER VISION
Time: 3 hrs. Max. Marks: 100 Note: Answer any FIVE full questions, choosing ONE full question from each module. Q. No. Questions Marks CL/COs Module 1 1 a. Discuss Geometric and transformations in 2D and 3D 8 CL3/CO b. Define^ Sampling^ and^ also^ explain^ Sampling^ and^ Sample^ point^ spread functions (PSF) with relevant diagrams.
7 CL2/CO
c. Explain basic lens models with relevant diagrams. 5 CL2/CO OR 2 a. (^) Discuss Photometric image formation with relevant diagrams. (^8) CL3/CO b. Explain Lens Distortion with relevant examples. 7 CL2/CO c. Write a short note on the following a. Diffuse reflection b. Specular reflection
5 CL2/CO
Module 2 (^3) a. Define Digital Image. To process the digital image what are^ key fundamental steps required explain with a neat block diagram.
CL2/CO
b. Define Digital Image. To process the digital image what are key fundamental steps required explain with a neat block diagram.
10 CL2/CO
OR
a. Describe Structure of eye and image formation in the eye^ with reference to human eye with relevant diagram. (^10) CL2/CO b. Consider the image segment shown. (a) Let V= {0,1} and compute the lengths of the shortest 4-, 8-, and m-path between p and q. If a particular path does not exist between these two points, explain why. (b) Repeat for V = {1,2}
10 CL2/CO^2
Module 3 5 a.^ Perform histogram matching of the image whose data is shown in following Table 5 a. & 5 a. Original Image Table 5a. Gary level 0 1 2 3 4 5 6 7 Number of pixels 8 10 10 2 12 16 4 2 Desired Image Table 5a. Gary level 0 1 2 3 4 5 6 7 Number of pixels 0 0 0 0 20 20 16 8
10 CL2/CO
b. Define 2-D Discrete Fourier Transform and discuss the properties of 2-D , DFT^10 CL2/CO OR 6 a.^ Perform histogram equalization of the 5x5 image whose data is shown in following Table.6a Table.6a Gary level 0 1 2 3 4 5 6 7 Number of pixels 0 0 0 6 14 5 0 0
10 CL 3 /CO
b. With necessary graphs, explain the following spatial image enhancement operations: i) Image negative ii) Log transformation iii) Power law transformation iv) Contrast stretching
10 CL2/CO
Module 4 7 a.^ Discuss various noise models in image degradation. 10 CL 3 /CO b. Write short note for the following. i. Image smoothing in spatial filtering ii. Image sharpening using frequency domain filters
10 CL2/CO
OR
a. (^) With relevant examples explain mean filters and order static filters in image restoration in spatial domain. (^10) CL 3 /CO b. Write short note for the following. i. Adaptive Local Noise filter with relevant equations ii. Adaptive median filter with relevant equations
10 CL2/CO
Module 5 9 a. (^) Explain the following with relevant diagram i. Opening and Closing ii. Hit or Miss Transform
CL2/CO
b. (^) Explain the Basic Morphological Algorithms. 10 CL2/CO OR (^10) a. (^) Explain the following Basic Morphological Algorithms. i) Boundary Extraction ii) Skeletons
CL2/CO
b. (^) Explain the following Representation w.r.t Boundary i) Boundary Following ii) Cain codes
10 CL2/CO
