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Home / Syllabus / B.E. (Artificial Intelligence and Data Science) / TY BE AI and DS / Semester 6 / Image and Video Processing

B.E. (Artificial Intelligence and Data Science) Image and Video Processing Syllabus - Mumbai University

This is the TY BE AI and DS syllabus under CBCS REV-2019 'C' Scheme, in force from the academic year 2022-23. The University has published no NEP 2020 syllabus for Semesters V to VIII of any engineering branch, so this is the scheme you are examined on — exam form 1T01815 and 1T01816. The first and second years of the degree are on NEP 2020.

Image and Video Processing.pdf
Semester 6 · TY BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

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Syllabus for Image and Video Processing

Semester 6 · TY BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

Module 1 04 hours

  • Digital Image Fundamentals
  • 1.1 Introduction to Digital Image, Digital Image Processing System, Sampling and Quantization,
  • 1.2 Representation of Digital Image, Connectivity, Image File Formats : BMP, TIFF and JPEG.

Module 2 08 hours

  • Image Enhancement in Spatial domain
  • 2.1 Introduction to Image Enhancement :Gray Level Transformations, Zero Memory Point Operations,
  • 2.2 Histogram Processing,.
  • 2.3 Neighbourhood Processing, Spatial Filtering, Smoothing and Sharpening Filters

Module 3 06 hours

  • Image Segmentation
  • 3.1 Segmentation based on Discontinuities (point, Line, Edge)
  • 3.2 Image Edge detection using Robert, Sobel, Previtt masks, Image Edge detection using Laplacian Mask.
  • 3.3 Region Oriented Segmentation: Region growing by pixel Aggregation, Split and Merge

Module 4 09 hours

  • Image Transforms
  • 4.1 Introduction to Unitary Transforms
  • 4.2 Discrete Fourier Transform(DFT), Inverse DFT, Properties of DFT, Fast Fourier Transform(FFT),
  • 4.3 Discrete Hadamard Transform(DHT), Inverse DHT, Fast Hadamard Transform(FHT), Discrete Cosine Transform(DCT), Inverse DCT

Module 5 08 hours

  • Image Compression
  • 5.1 Introduction, Redundancy, Fidelity Criteria
  • 5.2 Lossless Compression Techniques : Run length Coding, Arithmetic Coding, Huffman Coding
  • 5.3 Lossy Compression Techniques: Improved Gray Scale Quantization, Vector Quantization

Module 6 04 hours

  • Digital Video Processing
  • 6.1 Introduction to Digital Video Processing, Sampled Video
  • 6.2 Composite and Component Video, Digital video formats and applications

Text Books

  • 1 Rafael C. Gonzalez and Richard E. Woods, ̳Digital Image Processing', Pearson Education Asia, Third Edition, 2009
  • 2 S. Jayaraman, E. Esakkirajan and T. Veerkumar, "Digital Image Processing" TataMcGraw Hill Education Private Ltd, 2009
  • 3 Anil K. Jain, "Fundamentals and Digital Image Processing", Prentice Hall of India Private Ltd, Third Edition
  • 4 S. Sridhar, "Digital Image Processing", Oxford University Press, Second Edition, 2012.
  • 5 Alan C. Bovik, "The Essential Guide To Video Processing" Academic Press,
  • 6 Yao Wang, Jorn Ostermann, Ya-Qin Zang, "Video Processing and Communications", Prentice Hall, Signal Processing series.

Useful Links

  • 1 https://swayam.gov.in
  • 2 https://nptel.ac.in/courses
  • 3 https://www.coursera.org * Suggestion: Laboratory work based on the above syllabus can be incorporated as amini project in CSM601: Mini-Project.

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Data Science), item 6.42 (R), under CBCS REV-2019 'C' Scheme, in force from the academic year 2022-23. Wording, module numbering and hours are as printed in that syllabus.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

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