JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD B.Tech IV IMAGE PROCESSING AND PATTERN RECOGNITION Previous Question Paper (November/December - 2018 - R15)
Note: This question paper contains two parts A and B. Part A is compulsory which carries 25 marks. Answer all questions in Part A. Part B consists of 5 Units. Answer any one full question from each unit. Each question carries 10 marks and may have a, b, c as sub questions.
Part A
What is meant by neighborhood criterion?
Answer
The neighborhood criterion defines the spatial relationship between pixels in an image, typically based on connectivity. It specifies which neighboring pixels (e.g., 4-neighbors or 8-neighbors) are considered part of a set or region, forming the basis for operations like region growing or boundary detection.
What are the applications of homomorphic filter?
Answer
Homomorphic filtering is primarily used for:
- Image enhancement: Improving the appearance of images with non-uniform illumination.
- Dynamic range compression: Reducing the dynamic range of an image while increasing contrast.
- Feature extraction: Separating the illumination component (low-frequency) from the reflectance component (high-frequency) to isolate structural details.
Write a mask for edge detection.
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Which morphological operation is equivalent of logic OR operation.
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What is redundancy? How does it relate to compression ratio?
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Compare lossy and loss less compressions.
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What is representation in image processing?
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What are the different descriptors?
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List the fundamental problems of pattern recognition systems.
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How is patterns classified based on distance function?
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Part B
Explain the fundamental steps of image processing with neat block diagram.
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Explain the design of a wiener filter for image restoration and compare it with inverse filter.
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Write a morphological algorithm for detecting discontinuities in image.
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Explain threshold based segmentation and compare it with region based segmentation.
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Draw a generalized block diagram for image compression model and explain the significance of each block in image processing.
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Explain the method of transform coding for image compression with suitable example.
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What is signature? How is this used to represent an image? Compare it with other methods.
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Explain how the boundary descriptors are used for image processing.
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Explain design concepts of pattern recognition with suitable examples.
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How are patterns recognized automatically? Explain with example.
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What is Baye’s classifier? How is this used for pattern recognition?
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