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Download GTU BE/B.Tech 2018 Winter 8th Sem New 2182006 Machine Vision Question Paper

Download GTU (Gujarat Technological University) BE/BTech (Bachelor of Engineering / Bachelor of Technology) 2018 Winter 8th Sem New 2182006 Machine Vision Previous Question Paper

This post was last modified on 20 February 2020

GTU BE/B.Tech 2018 Winter Question Papers || Gujarat Technological University


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GUJARAT TECHNOLOGICAL UNIVERSITY
BE - SEMESTER-VIII (NEW) EXAMINATION — WINTER 2018

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Subject Code: 2182006 Date: 15/11/2018
Subject Name: Machine Vision
Time: 02:30 PM TO 05:00 PM Total Marks: 70

Instructions:

  1. Attempt all questions.
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  3. Make suitable assumptions wherever necessary.
  4. Figures to the right indicate full marks.

MARKS

Q.1 (a) Define histogram for a digital image. 03

(b) Explain the Digital image. 04

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(c) Compare and contrast various methods of zooming and shrinking the digital image. 07

Q.2 (a) Explain Sampling. 03

(b) Explain that the histogram equalization process is used for image enhancement. 04

(c) Briefly discuss the following logic operations based on morphology: NOT, AND, OR, XOR, NOT-AND 07

OR

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(c) Show that the 2-D Discrete Fourier Transform can be computed by successive computations of two 1-D Discrete Fourier Transform one after the other, one for all rows and the other for all columns. 07

Q.3 (a) Explain Sensor strip. 03

(b) Differentiate between erosion and dilation process. 04

(c) Explain the working of Laplacian filter in spatial domain. Also differentiate between the working of Laplacian filter and High Boost filter. 07

OR

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Q.3 (a) Explain Single sensor. 03

(b) Differentiate between high pass and low pass filters. 04

(c) Describe a complete digital image filtering process, in which illumination-and reflectance components of the image are separated out for further image processing. 07

Q.4 (a) What is Huffman coding? 03

(b) Explain the Gray level slicing. 04

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(c) Schematically represent the following transformations and their inverses illustrating their needs for specific application on digital image. 07

  1. Identity transformation
  2. Logarithmic transformation
  3. Power law transformation

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OR

Q.4 (a) What is LZW coding? 03

(b) Explain the Bit plane slicing. 04

(c) Evaluate the following statements. 07

  1. Laplacian filtered image gives blurred image when histogram equalization is applied to it.
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  3. Iso-preference curves tend to become more vertical as the details in the image increases

Q.5 (a) Explain Quantization. 03

(b) Describe the following properties of Fourier transform: Translation, Rotation. 04

(c) Explain with suitable example: “Instead of using histogram directly for image enhancement, one can use some statistical parameters also for image enhancement. 07

OR

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Q.5 (a) Explain the Euclidean distance measuring function between pixels of digital image. 03

(b) Describe the difference between opening and closing morphological operations which are performed on digital image. 04

(c) Describe Hit-or-Miss transform with the help of suitable example. 07

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