MCS-230 Solved Assignment 2025-26

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MCSL-230 Solved Assignment 2025-26 Available

Q1: Explain the Optical, Analog and Digital Image processing.

Q2:(1) What should be the physical size of a 2D image of a document with dimensions is 3200×2400, when scanned at 400dpi. Here dpi stands for dots per inch

(ii) If the physical size of a medical image is 4 * 4 inches and the sampling resolution is 5 cycles/mm, then how many pixels per cycle are required to have a better-quality image? Will an image of size 512×512 be enough?

Q3:(i) What is the storage requirement for a 2048 x 2048, 24-bitcolour image?

(ii) Explain Intensity, Contrast, Brightness, Noise and Resolution with respect to Images.

Q4:(1) Check whether the matrix A = 1/(sqrt(2)) * [[1, 2], [- 2, 1]] is unary or not?

(ii) Perform the transformation g_{1}(v) = 3v on the image f(x, y) = [[- 2, – 1, 0], [0, 1, 2]]

Q5: Apply given 3×3 mask w on the following image F (x, y) to generate the new image.

F(x, y) = [[10, 3, 1, 2, 20], [2, 4, 7, 2, 2], [5, 4, 2, 3, 6], [1, 4, 5, 3, 7], [6, 1, 6, 5, 0]] w(i, j) = 1/9 * [[1, 1, 1], [1, 1, 1], [1, 1, 1]]

Q6: What is a histogram? Find histogram of image given below:

Q7: Why is DCT important for image compression? Explain with the help of an example.

Q8: What do you understand by Image enhancement? Explain the techniques of image enhancement with a suitable example. Also discuss the advantages of image enhancement.

Q9: Explain the following Smoothing Filter(s):

(1) Ideal Low Pass Filters (ILPF)

(ii) Butterworth Low Pass Filters

(ii) Gaussian Low Pass filters (GLPF)

Q10: What do you understand by feature extraction? What are its applications? Also discuss few traditional methods of feature extraction.

(BLPF)

Q11:Explain image degradation and its types.

Q12:Transform the RGB cube by its CMY cube. Label all the vertices. Also, interpret the colours at the edges with respect to saturation.

Q13:Do you mean by Camera Calibration? Explain how intrinsic and extrinsic parameters of a camera are estinated?

Q14: Explain Bayesian Classification with the help of a suitable example.

Q15:Explain K-means clustering methods with the help of a suitable example. Also, discuss the advantages and disadvantages of k-means clustering methods.

Q16:Perform partitional clustering using Frogy’s method for the data given in the table below with k-2 (two clusters). Use first two sample points (3,3) and (6.8) as seed points.