IGNOU MCS 230 SOLVED ASSIGNMENT 2025

Ques 1.

What is image acquisition? Explain Optical, Analog and Digital image processing in brief.

Ques 2.

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?

Ques 3.

Solve the following problems:

a. What is the storage requirement for a 2024 x 2024, 24-bit colour image?

b. Calculate pixel resolution of a camera in mega pixels, capturing an image of dimension: 3000 X 4000

c. Given an image is a gray scale image with aspect ratio of 8:2 and pixel resolution of 1000000 pixels, calculate the dimensions and the size of the image.

Ques 4.

Explain how image enhancement is better in the frequency domain as compared to spatial domain.

Ques 5.

(i) Ideal Low Pass Filters (ILPF) (ii) Butterworth Low Pass Filters (BLPF) (iii) Gaussian Low Pass filters (GLPF)

Ques 6.

Explain the following Smoothing Filter(s):

Ques 7.

 Explain the following Image Sharpening Filter(s):

Ques 8.

i) Ideal High Pass Filters (ILPF) () Butterworth High Pass Filters (BLPF)   (iii) Gaussian High  Pass filters (GLPF)

Ques 9.

Explain Mean Filters, and Median Filter with the help of a suitable example for each.

Ques 10.

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

Ques 11.

Explain optical flow, in context of motion perception in computer vision.

Ques 12.

Explain epipolar geometry with the help of a suitable diagram in stereo vision system.

Ques 13.

What is camera calibration? Explain how it helps to estimate the intrinsic and extrinsic parameters of a camera.

Ques 14.

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

Ques 15.

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.

Ques 16.

Explain agglomerative hierarchical clustering and its types with the help of a suitable example.

Ques 17.

Explain Bayes classifier with the help of a suitable example. Also discuss its properties.

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