STUPIDSID
Solve any one question from Q.1(a,b)& Q2.(a,b)
1(a)
Explain the Human Visual system in detail.
4 M
Solve any one question from Q.1(a,b) & Q.2(a,b)
1(a)
Explain the Human Visual system in detail.
4 M
1(b)
Explain in brief & with example three disatance measures between pixels.
3 M
1(b)
Explain in brief & with example three distance measures between pixels.
3 M
2(a)
What is image subtraction? How the pixels are scales between 0 to 255 after image subtraction. Give application of image subtraction operation.
4 M
2(a)
What is image subtraction? How the pixels are scaled between 0 to 255 after image subtraction. Give application of image substraction operation.
4 M
2(b)
Explain HSI color model of an image.
3 M
2(b)
Explain HSI color model of an image
3 M
Solve any one question from Q.3(a,b)& Q.4(a,b)
3(a)
Filter the following image using 3×3 neighbourhood averaging by assuming zero padding. \( \begin{bmatrix}
1& 2 & 3& 2\\
4 & 2& 5 & 1\\
1 & 2 & 6 & 3\\
2 & 4 & 6 & 7
\end{bmatrix} \)/
4 M
Solve any one question from Q.3(a,b) & Q.4(a,b)
3(a)
Filter the following image using 3×3 neighbourhood averaging by assuming zero padding. \[\begin{bmatrix}
1 &2 &3 &2 \\
4 & 2 & 5 & 1\\
1 &2 & 6 & 3\\
2 &4 & 6 &7
\end{bmatrix}\]
4 M
3(b)
Explain any three noise models in short.
5 M
3(b)
Explain any three noise models in short.
5 M
4(a)
Explain following operations of image enhancement.
i) Power law transformation.
ii) Contrast streching.
i) Power law transformation.
ii) Contrast streching.
4 M
4(a)
Explain following operations of image enhancement.
i) Power law transformation.
ii) Contrast streching.
i) Power law transformation.
ii) Contrast streching.
4 M
4(b)
Explain the concept of Homomorphic filtering.
3 M
4(b)
Explain the concept of Homomorphic filtering.
3 M
Solve any one question from Q.5(a,b)& Q.6(a,b)
5(a)
Compute the entropy of the image given by \( f(x,y)=\begin{bmatrix}
0& 1& 0 &0 \\
0 & 1& 2&2 \\
0& 1 & 2 & 3\\
1 & 2 & 2 & 3
\end{bmatrix} \)/
4 M
Solve any one question from Q.5(a,b) & Q.6(a,b)
5(a)
Compute the entropy of the image given by \[f(x,y)=\begin{bmatrix}
0 & 1& 0 & 0\\
0& 1& 2 & 2\\
0 & 1 & 2& 3\\
1& 2 & 2 & 3
\end{bmatrix}\]
4 M
5(b)
Explain the concept of bit plane coding.
3 M
5(b)
Explain the concept of bit plane coding.
3 M
6(a)
Draw the block diagram of JPEG base line encoder. Explain each block in short.
4 M
6(a)
Draw the block diagram of JPEG base line encoder. Explain each block in short.
4 M
6(b)
Define Lossless & Lossy compression. Explain with example how Runlenght coding technique is used for Lossless Compression.
3 M
6(b)
Define Lossless & Lossy compression. Explain with example how Runlenght coding technique is used for Lossless Compression.
3 M
Solve any one question from Q.7(a,b)& Q.8(a,b)
7(a)
What is edge detection? Compare the performance of first order & second order derivative w.r.t. an image? Which one would you prefer for detecting edges? Why?
9 M
Solve any one question from Q.7(a,b) & Q.8(a,b)
7(a)
What is edge detection? Compare the performance of first order & second order derivative w.r.t. an image? Which one would you prefer for detecting edges? Why?
9 M
7(b)
Define image segmentation. What is Region based apporach for image segmentation Explain Region growing & Region splitting and merging technique in detail.
9 M
7(b)
Define image segmentation. What is Region based approach for image segmentation Explain Region growing & Region splitting and merging technique in detail.
9 M
8(a)
Explain the following in detail.
i) Hough transform
ii) Hit or Miss transform
i) Hough transform
ii) Hit or Miss transform
10 M
8(a)
Explain the following in detail.
i) Hough transform
ii) Hit or Miss transform
i) Hough transform
ii) Hit or Miss transform
10 M
8(b)
Explain Global, adaptive and otsu's method of thresholding.
8 M
8(b)
Explain Global, adaptive and otsu's method of thresholding.
8 M
Solve any one question from Q.9(a,b)& Q.10(a,b)
9(a)
What is the need of boundary descriptor. Explain 4-directional & 8-directional chain code with example. Hence obtain the project shape represented by 8-directional chain code (clock wise)
{0, 1, 5, 0, 6, 6, 4, 4, 4, 4, 2, 2}
{0, 1, 5, 0, 6, 6, 4, 4, 4, 4, 2, 2}
8 M
Solve any one question from Q.9(a,b) & Q.10(a,b)
9(a)
What is the need of boundary descriptor. Explain 4-directional & 8-directional chain code with example. Hence obtain the object shape represented by 8-directional chain code(clock wise) {0, 1, 5, 0, 6, 6, 4, 4, 4, 4, 2, 2}
8 M
9(b)
Explain the following Regional descriptors
i) Topological Descriptors ii) Texture descriptors
i) Topological Descriptors ii) Texture descriptors
4 M
9(b)
Explain the following Regional descriptors
i) Topological Descriptors
ii) Texture descriptors
i) Topological Descriptors
ii) Texture descriptors
8 M
10(a)
Explain in detail the concept of Fourier descriptor based boundary representation. What are its advantages.
8 M
10(a)
Explain in detail the concept of Fourier descriptor based boundary representation. What are its advantages
8 M
10(b)
Explain in detail the following
i) Staistical moments
ii) Principle component Analysis.
i) Staistical moments
ii) Principle component Analysis.
8 M
10(b)
Explain in detail the following
i) Statistical moments
ii) Principle component Analysis
i) Statistical moments
ii) Principle component Analysis
8 M
Solve any one question from Q.11(a,b)& Q.12(a,b)
11(a)
What is Pattern? Explain the representation of different pattern classes.
8 M
Solve any one question from Q.11(a,b) & Q.12(a,b)
11(a)
What is Pattern? Explain the representation of different pattern classes.
8 M
11(b)
Explain Biometric based Authentication system using image processing.
8 M
11(b)
Explain Biometric based Authentication system using image processing.
8 M
12(a)
Explain Minimum distance classifiers and correlation based classifier in detail.
8 M
12(a)
Explain Minimum distance classifiers and correlation based classifier in detail
8 M
12(b)
Explain Medical application of image processing in detail.
8 M
12(b)
Eplain Medical application of image processing in detail.
8 M
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