GTU BE 8th Semester 182006 Machine Vision (Department Elective – II) Summer 2018 Question Paper

1
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE – SEMESTER ?VIII (old) – EXAMINATION ? SUMMER 2018
Subject Code:182006 Date:07/05/2018
Subject Name:Machine Vision (Department Elective – II)
Time:10:30 AM to 01:00 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 (a) Explain the following terms briefly.
Digital image, Sampling, Quantization
07
(b) With the help of suitable example describe the application of image blurring.
07

Q.2 (a) Briefly describe the working principle of median filter, max filter and min filter.

07
(b) Explain the role of Isopreference curves to decide the quality of digital images
with different amount of details.
07
OR

(b) Bring out the limitation of human vision system by comparing it with the
working of digital camera.
07

Q.3 (a) Explain various transfer functions which are used for the applications of image
enhancement in spatial domain.
07
(b) Describe the morphological process of image dilation. Give suitable example of
image enhancement using dilation process.
07
OR

Q.3 (a) Explain the working principle of high pass filters and low pass filters for image
enhancement in frequency domain.
07
(b) Describe the difference between opening and closing morphological operations
which are performed on digital image.
07

Q.4 (a) Define histogram of a digital image. Describe various contrast stretching
operations for different types of histograms.
07
(b) Explain the following terms in relation with digital image processing.
Bit plane slicing; Gray level slicing
07 1
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE – SEMESTER ?VIII (old) – EXAMINATION ? SUMMER 2018
Subject Code:182006 Date:07/05/2018
Subject Name:Machine Vision (Department Elective – II)
Time:10:30 AM to 01:00 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 (a) Explain the following terms briefly.
Digital image, Sampling, Quantization
07
(b) With the help of suitable example describe the application of image blurring.
07

Q.2 (a) Briefly describe the working principle of median filter, max filter and min filter.

07
(b) Explain the role of Isopreference curves to decide the quality of digital images
with different amount of details.
07
OR

(b) Bring out the limitation of human vision system by comparing it with the
working of digital camera.
07

Q.3 (a) Explain various transfer functions which are used for the applications of image
enhancement in spatial domain.
07
(b) Describe the morphological process of image dilation. Give suitable example of
image enhancement using dilation process.
07
OR

Q.3 (a) Explain the working principle of high pass filters and low pass filters for image
enhancement in frequency domain.
07
(b) Describe the difference between opening and closing morphological operations
which are performed on digital image.
07

Q.4 (a) Define histogram of a digital image. Describe various contrast stretching
operations for different types of histograms.
07
(b) Explain the following terms in relation with digital image processing.
Bit plane slicing; Gray level slicing
07
2

OR

Q.4 (a) Explain the working of following filters with its mathematical equation.
Alpha trim filter; Contra harmonic filter
07
(b) Briefly describe the following properties of Fourier transform.
Separability; Translation
07

Q.5 (a) Differentiate between arithmetic and logical operators for digital image
processing with the help of suitable examples.
07
(b) Describe and differentiate between band pass and band reject filters used in
frequency domain for image restoration. Support your answer with the neat
schematic diagrams of these filters.
07
OR

Q.5 (a) Compare the working principle of general averaging filter with adaptive local
noise reduction filter.
07
(b) Explain the procedure to get a sharpened image using Laplacian filter in
frequency domain. Derive Laplacian filter in frequency domain to support your
answer.
07
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