Exam Details
| Subject | elective – i : computer vision | |
| Paper | ||
| Exam / Course | f.y. m.tech. (civil -structural engg.) | |
| Department | ||
| Organization | solapur university | |
| Position | ||
| Exam Date | 12, December, 2018 | |
| City, State | maharashtra, solapur |
Question Paper
F.Y. M.Tech. (Computer Science and Engineering) (Semester
(New CBCS) Examination, 2018
Elective I Computer vision
Day and Date Wednesday, 12-12-2018 Total Marks 70
Time 10.00 a.m. to 1.00 p.m.
Instructions Question 1 and 5 are compulsory.
Attempt any two questions from question 2 to 4 from
Section I.
Attempt any two questions from question 6 to 8 from
Section II.
Figures to the right indicate marks to a question.
Assume suitable data wherever necessary.
Section I
1. Explain simplified model of photographic image formation. 10
Explain different applications where computer vision is used. 5
2. Explain main factors affecting the performance of a digital image sensor. 5
Explain different morphological operations. 5
3. Explain 2D geometric transformations. 5
Explain how thresholding is used in segmentation. 5
4. Explain different distance functions used for feature matching. 5
E xplain processing stages occurred in modern digital camera. 5
Set P
SLR-MT 38 *SLRMT38*
Set P
Section II
5. Explain basic feature detection algorithm and feature descriptors. 10
Explain different measures used in feature matching. 5
6. Explain supervised, unsupervised and semi-supervised classification. 5
Explain computational photography in detail. 5
7. Explain how features are reduced using Linear discriminant Analysis. 5
Explain K-Medoids Clustering algorithm. 5
8. Explain different types of biometrics. 5
Explain voice recognition in detail. 5
(New CBCS) Examination, 2018
Elective I Computer vision
Day and Date Wednesday, 12-12-2018 Total Marks 70
Time 10.00 a.m. to 1.00 p.m.
Instructions Question 1 and 5 are compulsory.
Attempt any two questions from question 2 to 4 from
Section I.
Attempt any two questions from question 6 to 8 from
Section II.
Figures to the right indicate marks to a question.
Assume suitable data wherever necessary.
Section I
1. Explain simplified model of photographic image formation. 10
Explain different applications where computer vision is used. 5
2. Explain main factors affecting the performance of a digital image sensor. 5
Explain different morphological operations. 5
3. Explain 2D geometric transformations. 5
Explain how thresholding is used in segmentation. 5
4. Explain different distance functions used for feature matching. 5
E xplain processing stages occurred in modern digital camera. 5
Set P
SLR-MT 38 *SLRMT38*
Set P
Section II
5. Explain basic feature detection algorithm and feature descriptors. 10
Explain different measures used in feature matching. 5
6. Explain supervised, unsupervised and semi-supervised classification. 5
Explain computational photography in detail. 5
7. Explain how features are reduced using Linear discriminant Analysis. 5
Explain K-Medoids Clustering algorithm. 5
8. Explain different types of biometrics. 5
Explain voice recognition in detail. 5
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