Q.1
14 Marks(b)
Define the term "radiometry" and explain its importance in computer vision.
(c)
Explain the concept of imaging geometry in computer vision. Discuss the principles of perspective projection.
Also asked in Summer 2026 Q2c OR
Gujarat Technological UniversitySummer 2025 examination
GTU 3171614 Computer Vision Summer 2025 Question Paper & PDF
B.E. · IT Engineering · Semester 7 · Subject code 3171614
- Total
- 70 marks
- To pass
- 23 marks (33%)
- Duration
- 2.5 Hours 2:30 PM – 5:00 PM
- Questions
- 5 with internal choice
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11 of 25 questions on this paper were also asked in other years. Each is marked below with the years it appeared.See all 17 repeated 3171614 questions, most asked first
Q.2
14 Marks(a)
How does the Fourier transformation play a role in image sharpening?
(b)
Define pixel. List all pixel transformation methods.
(c)
What is histogram? Explain histogram equalization algorithm. Write Matlab code for calculation of histogram and histogram equalization.
Also asked in Summer 2026 Q2b, Winter 2025 Q2c
OR
(c)
Implement the various low pass and high pass filtering mechanisms.
Also asked in Winter 2025 Q5a, Winter 2025 Q5a OR
Q.3
14 Marks(a)
Write use of SIFT and HOG in terms of image analysis.
(b)
Explain the watershed algorithm and its application in image segmentation.
Also asked in Summer 2026 Q4b OR, Winter 2025 Q4c
(c)
Demonstrate the use of optical flow in any image processing application.
OR
(a)
Define the terms: Image Digitization, Normalized cut and kernel
(b)
Describe the split and merge algorithm in image segmentation. How does it work?
Also asked in Summer 2026 Q4b, Winter 2025 Q4c OR
(c)
Briefly describe snake’s method for active contours.
Also asked in Summer 2026 Q4c OR, Winter 2025 Q3b
Q.4
14 Marks(a)
Explain the concept of optical flow in motion representation and its applications.
Also asked in Winter 2025 Q5c
(b)
What are intrinsic and extrinsic camera parameters in camera calibration, and how are they determined?
(c)
Explain K-means and Gaussian Mixture Model in detail.
OR
(a)
What is regularization in motion representation, and why is it important?
(c)
What is noise? List all types of noise and explain any four in detail.
Q.5
14 Marks(a)
Explain graph based segmentation.
(b)
Define appearance-based methods for object recognition and provide an example.
OR
(a)
Explain the concept of image Eigen spaces and their use in object recognition.
(b)
Explain shape context descriptor.
(c)
Describe common camera projection models and discuss their strengths and limitations in representing the real world.
Also asked in Winter 2025 Q4b
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About this paper
Official Gujarat Technological University (GTU) examination paper for Computer Vision (Summer 2025, B.E. · IT Engineering, Sem 7). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.