Questions Search

This website covers previous years question papers of various universities and colleges in India. Moreover, the information on admission to various courses from various universities/institutes/colleges are also available. Research paper questions are also updated from time to time. Also the latest teaching faculty plus teachers jobs, Government jobs, Banking Jobs, and other jobs are regularly updated to help jobless candidates. Admit cards of various recruitment of Govt organisation are updated. Search your terms using the search box provided.

Follow by Email

Tuesday, November 22, 2016

IT6005 Digital Image Processing Nov Dec 2016 Important Questions

Important questions / expected questions for Nov Dec 2016 IT6005 Digital Image Processing examinations conducting by Anna University Chennai
B.E./ B.Tech. DEGREE EXAMINATION Nov Dec 2016
07th Semester / Seventh Semester / IVYear
Department of ECE
IT6005 Digital Image Processing
(Regulation 2013)
Nov Dec 2016 Important Questions

Important 16 Marks Questions with answers (All five units) are listed for IT6005 Digital Image Processing subject

1. (i) Explain the human visual perception system in detail with necessary diagrams. (10)
(ii) Explain CMY and CMYK colour models (6)
2. i) Explain in detail about image acquisition system (8)
ii) Illustrate how the image is digitized by sampling and quantization process (8)
3. Distinguish the following terms and brief each:
i) Adjacency ii) Connectivity iii) Region iv) Boundary (4*4=16)
4. Evaluate the various colour models. Explain each of them in detail.
5. Analyze the various parameters of image processing
i) Band number ii) Spectrum, iii) wave lengths, iv) applications.  (4*4=16)
6. i) State and explain sampling theorem in 2D (10)
ii) Write about aliasing in Images (6)
7. i) Explain the histogram equalization method of image enhancement. (8)
ii) Explain histogram specification technique in detail with equations.  (8)
8. Write detail note about
i) Spatial domain enhancement (8)
ii) Frequency domain enhancement (8)
9. i) With example explain in detail about spatial averaging. (8)
ii) Describe in detail about various types of mean filters. (8)
10. i) Compare smoothing & sharpening in frequency domain (4)
ii) Analyze the performance of following smoothing filters
Ideal Low Pass Filter (4)
Butterworth Low Pass Filter (4)
Gaussian Low Pass Filter (4)
11. i) Sketch the block diagram for image degradation model and explain (8)
(ii) Explain the use of wiener filtering in image restoration (8)
12. Develop the algorithm for following filtering
(i) Inverse filtering (8)
(ii) LMS filter (8)
13. Describe inverse filtering for removal of blur caused by any motion and describe how it restore the image (16)
14. (i) What do you mean by optimal thresholding in detail and how do you obtain the threshold for image processing(8)
(ii) Different types of thresholding for segmentation (8)
15. Describe constrained least square filtering for image restoration and derive its transfer function (16)
16. Solve and find a source emits letters from an alphabet A={a1,a2,a3,a4,a5} with probabilities P(a1)==0.2, P(a2)=0.4, P(a3)=0.2, P(a4)=0.1 and P(a5)=0.1
(i) Find a Huffman code for this source?
(ii) Find the average length of the code and its redundancy?
17. Write short notes on:
(ii) Arithmetic coding. (8)
(iii) JPEG standards. (8)
18. Evaluate the need for image compression. How run length encoding approach is used for compression? Is it lossy? Justify
19. Explain in detail about
(i) Bit plane coding (8)
(ii) LZW coding (8)
20. State the basic concepts of the following terms
(i) Haar transform (5)
(ii) Subband coding (5)
(iii) Fast wavelet transform (6).
21. i) Explain the concepts and approach of chain code (10)
ii) Boundary representation (6)
22. Explain the different types of boundary descriptors with suitable diagrams
23. State the concepts of following methods
i) Signature (5)
ii) Boundary segments (5)
iii) Skeletons (6)
24. Write in detail note about the following
i) Textures (4)
ii) Shape numbers (4)
iii) Fourier descriptors (4)
(iv) Pattern classes (4)
25. Explain the structural methods of object recognition
i) Matching shape numbers
(ii) String matching

No comments:

Post a Comment

Pen down your valuable important comments below