VTU CSE 7th Semester Digital Image Processing Question Paper January 2013: To score better marks in the 7th semester, you should also have depth knowledge in the entire subject. You can boost your preparation by solving previous year question papers. It will give you information about the important chapters and concepts to be covered in all chapters.
Here we are providing you the complete guide on Digital Image Processing Question Paper January 2013.
VTU CSE 7th Semester Digital Image Processing Question Paper January 2013
You should practice as many questions as possible along with other study materials. It will help you to secure better marks in the semester exam.
You must have Digital Image Processing Question Paper along with the latest Computer Science 7th sem Syllabus to enhance your semester exam preparation.
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Here you can check the VTU CSE 7th Semester Digital Image Processing Question Paper January 2013
Note: Answer FIVE full questions selecting at least TWO questions from each part.
1 a. Define an image. Explain t he various components of a general — purpose image processing system,
b. Explain so me of the basic relationships that exists between pixels in a digital image.
2 a. Explain the concept of sampling and quantization of an image. Explain how images are
b. How is image formed in an eye? Explain the importance of brightness adaptation and discrimination in image processing?
3 a. Explain how image segmentation algorithms are categorized. Discuss how point detection and line detection algorithms works.
b. Briefly explain the different phases of canny edge detector. Differentiate between canny edge and Laplacian of Gaussian edge detector.
4 a. Explain the concept of edge linking by using global processing via the Hough transform.
b. Explain with different steps, the working of region based segmentation algorithm.
5 a. The basic approach used to approximate a discrete derivative involves taking difference of the form + I, y) – f(x. y).
i) Obtain the filter transfer function, H(u, v) for performing the equivalent process in the frequency domain
ii) Show’ that H(u, v) is a high pass filter.
b. How is smoothing achieved in the frequency domain. Explain the three types (basic) of LPE?.
6 a. With a flow diagram explain how homorphic filtering approach is used for image enhancement.
b. With a neat diagram, explain a lossless predictive coding model used for image compression.
7 a. Define chain codes. Explain the three different types of polygonal approximations techniques?
b. Along with the mathematical formulation, explain the various regional descriptors.*!o Marks)
8 a. Define the opening and closing. List the properties of opening and closing operations.
b. Explain some of the basic morphological algorithms?
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