AKTU Image Analytics (BCDS061) Question Paper 2024-25

Note: Attempt all Sections. In case of any missing data; choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

1. What are the main characteristics of a histogram in an image?
2. List different kind of filters.
3. What is the Hit-or-Miss transform used for?
4. Name two basic morphological algorithms and their applications.
5. Define pseudo color image processing.
6. List two preprocessing steps used for boundary detection.
7. What are the key components of a convolution neural network (CNN)?

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

1. What is morphological reconstruction? Explain its steps and applications with an example.
2. Define image smoothing and image sharpening. How do they differ in the context of color image processing?
3. List advantages of using deep learning over traditional pattern classification techniques.
4. What is the purpose of feature extraction in image analysis?
5. Discuss the working and applications of smoothing spatial filters with examples like averaging and Gaussian filters.

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

1. Describe image segmentation using region growing and region splitting & merging methods. Compare their efficiency.
2. Describe the steps involved in the Scale-Invariant Feature Transform (SIFT) algorithm. What makes it robust?

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

1. Compare and contrast binary morphology and grayscale morphology. Provide use cases for each.
2. Describe the minimum-distance classification algorithm. Derive the decision rule and illustrate with an example.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain the fundamental steps involved in a digital image processing system with a block diagram.
2. Explain the architecture and learning process of multilayer feed forward neural networks. How does back propagation work?

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

1. Write and explain a Python/MATLAB program to perform erosion, dilation, opening, and closing operations on a binary image.
2. Explain prototype matching using 2D correlation and discuss its application in template-based recognition.

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

1. Discuss various types of pixel relationships and their importance in image processing.
2. Explain boundary representation and its significance in object recognition. What are the different techniques used?

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