Acharya Nagarjuna University Question Paper
Course: B Tech Computer Science and Engineering
[Total No. of Questions : 09]
CS/IT 326 (CR)
3/4 B.Tech Degree Examinations, March / April 2016
Second Semester
CS/IT
Computer Vision
Time : 3 hours
Maximum Marks : 70
Answer question No.1 Compulsory
Answer ONE question from each Unit
1. Briefly explain following [7 x 2 = 14M]
a) What is an image?
b) Edge detection techniques
c) Define segmentation
d) Region properties
e) Inverse perspective projection
f) 2D Vs 3D.
g) Define facet.
h) What is a computer vision?
i) Photogrammetry
j) What is thinning?
k) Techniques for matching.
l) External points
m) Morphological operators for edge detection.
n) Global Vs local features.
UNIT - I [1 x 14 = 14M]
2. Explain the different image pre-processing stages that can be used in a computer vision system. (OR)
3. Explain the important morphological operations: Dilation, Erosion, Opening and Closing in detail. How can these are used in obtaining skeleton of an image.
UNIT - II [1 x 14 = 14M]
4. Explain various techniques used for region analysis. (OR)
5. What is the basic concept in Hough transform? How is Hough transform used in line detection.
UNIT - III [1 x 14 = 14M]
6. a) Give the classification of shapes by labeling of edges.
6. b) Explain back tracking algorithms with suitable examples. (OR)
7. Describe intensity of matching of 1 dimensional and 2 dimensional signals.
UNIT - IV [1 x 14 = 14M]
8. Briefly explain about ordered structural matching with suitable examples. (OR)
9. Discuss about various control strategies in knowledge based vision.
Course: B Tech Computer Science and Engineering
[Total No. of Questions : 09]
CS/IT 326 (CR)
3/4 B.Tech Degree Examinations, March / April 2016
Second Semester
CS/IT
Computer Vision
Time : 3 hours
Maximum Marks : 70
Answer question No.1 Compulsory
Answer ONE question from each Unit
1. Briefly explain following [7 x 2 = 14M]
a) What is an image?
b) Edge detection techniques
c) Define segmentation
d) Region properties
e) Inverse perspective projection
f) 2D Vs 3D.
g) Define facet.
h) What is a computer vision?
i) Photogrammetry
j) What is thinning?
k) Techniques for matching.
l) External points
m) Morphological operators for edge detection.
n) Global Vs local features.
UNIT - I [1 x 14 = 14M]
2. Explain the different image pre-processing stages that can be used in a computer vision system. (OR)
3. Explain the important morphological operations: Dilation, Erosion, Opening and Closing in detail. How can these are used in obtaining skeleton of an image.
UNIT - II [1 x 14 = 14M]
4. Explain various techniques used for region analysis. (OR)
5. What is the basic concept in Hough transform? How is Hough transform used in line detection.
UNIT - III [1 x 14 = 14M]
6. a) Give the classification of shapes by labeling of edges.
6. b) Explain back tracking algorithms with suitable examples. (OR)
7. Describe intensity of matching of 1 dimensional and 2 dimensional signals.
UNIT - IV [1 x 14 = 14M]
8. Briefly explain about ordered structural matching with suitable examples. (OR)
9. Discuss about various control strategies in knowledge based vision.
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