07A80504 Image Processing B.Tech Question Paper : scce.ac.in
Name of the College : SREE CHAITANYA COLLEGE OF ENGINEERING
University : JNTUH
Department : Computer Science And Engineering
Subject Code/Name : 07A80504/IMAGE PROCESSING
Year/Sem : IV/I
Website : scce.ac.in
Document Type : Model Question Paper
Download Model/Sample Question Paper : https://www.pdfquestion.in/uploads/scce.ac.in/4958-07A80504%20IMAGE%20PROCESSING.pdf
Image Processing Question Paper :
B.Tech IV Year II Semester Examinations, April/May-2012
(COMPUTER SCIENCE AND ENGINEERING)
Time: 3 hours
Related : Sree Chaitanya College Of Engineering 07A80506 Distributed Databases B.Tech Question Paper : www.pdfquestion.in/4957.html
Max. Marks: 80
Answer any five questions :
All questions carry equal marks :
1. What are the fundamental steps in image processing? Explain them in detail with some examples. [16]
2. Explain the following image enhancement methods:
a) Bit-plane slicing b) Image negative
c) Contrast stretching d) Log transformation. [4×4=16]
3.a) Draw the degradation model and give the reasons for degradation.
b) How is an inverse filter used for image restoration in presence of noise? [8+8]
4.a) Write a short note on color fundamentals in image processing.
b) Explain segmentation process in HIS color space. [8+8]
5.a) What is redundancy? How to measure it?
b) How is a prediction coding used for lossy image compression? [8+8]
6.a) What are skeletons? How it is used in image processing?
b) Give result of logical operations on an image. [8+8]
7. Explain the region based segmentation in detail with examples. [16]
8.a) Explain how image correlation is used for recognization.
b) Specify the structure and weights of a neural network capable of performing exactly the same function as a minimum distance classifier for two pattern classes in n-dimensional space. [8+8]
SET 2R07
Code No: 07A80504
1. What are the different components of image processing? Explain the function of each with suitable examples. [16]
2.a) What is point processing? How is it used in image enhancement?
b) Explain how a spatial high pass filter is used for image enhancement. [8+8]
3.a) What are the different noises present in image? How to represent them?
b) How is a wiener filter used for image restoration? [8+8]
4.a) How to convert HSI color model to RGB color model?
b) What are the various color space components in full color image?
c) What is color slicing? Give some examples. [6+5+5]
5.a) Explain the following with respect to an image:
i) Inter pixel redundancy ii) Psychovisual redundancy
iii) Coding redundancy iv) Fidelity criteria.
b) Explain how Huffman coding is used for image compression? [8+8]
6.a) How a boundary of an image can be extracted by morphological processing?
b) What are the applications of Morphological opening and closing operations? [8+8]
7. Explain in detail how a point, line and edge can be detected in an image. [16]
8.a) Explain recognition techniques based on matching.
b) Give an expansive tree grammar for generating images consisting of alternating 1’s and 0’s in both spatial directions ( in checkerboard pattern). Assume that the top left element is a 1 and that all images terminate with a 1 as the bottom left element. [8+8]
B.Tech IV Year II Semester Examinations, April/May-2012 :
Image Processing :
1.a) How can an image be sampled?
b) What is meant by neighborhood criteria in an image?
c) Explain different connectivity methods in an image. [5+5+6]
2.a) Explain Histogram equalization method for an image enhancement.
b) What are the different Arithmetic and logic operators used in image enhancement? [8+8]
3.a) How a constrained least square filter is used for image restoration? What are advantages of it compared to wiener filter?
b) How to estimate the degradation function? [10+6]
4.a) How a RGB color model convert into HSI model?
b) Explain smoothing of color image based on neighborhood averaging method. [8+8]
5.a) What are fidelity criteria? How is it used in an image processing?
b) Explain one and two dimensional run-length codes used for image compression. [6+10]
6. Explain the following with respect to image processing:
a) Hit-or-Miss transformation b) Thinning and Thickening. [8+8]
7.a) Explain how a gradient operator can be used to detect an edge?
b) Explain the region splitting and merging procedure for image segmentation.[8+8]
8.a) Explain how a string matching is used for recognization.
b) Specify the structure and weights of a neural network capable of performing exactly the same function as a Bayes classifier for two pattern classes in n- dimensional space. The classes are Gaussian with different means but equal covariance matrices. [8+8]