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Digital Image Processing Semester 6 (TE Third Year) BE Biomedical Engineering University of Mumbai Topics and Syllabus

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University of Mumbai Syllabus For Semester 6 (TE Third Year) Digital Image Processing: Knowing the Syllabus is very important for the students of Semester 6 (TE Third Year). Shaalaa has also provided a list of topics that every student needs to understand.

The University of Mumbai Semester 6 (TE Third Year) Digital Image Processing syllabus for the academic year 2021-2022 is based on the Board's guidelines. Students should read the Semester 6 (TE Third Year) Digital Image Processing Syllabus to learn about the subject's subjects and subtopics.

Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the University of Mumbai Semester 6 (TE Third Year) Digital Image Processing Syllabus pdf 2021-2022. They will also receive a complete practical syllabus for Semester 6 (TE Third Year) Digital Image Processing in addition to this.

CBCGS [2018 - current]
CBGS [2014 - 2017]
Old [2000 - 2013]

University of Mumbai Semester 6 (TE Third Year) Digital Image Processing Revised Syllabus

University of Mumbai Semester 6 (TE Third Year) Digital Image Processing and their Unit wise marks distribution

University of Mumbai Semester 6 (TE Third Year) Digital Image Processing Course Structure 2021-2022 With Marking Scheme

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Syllabus

100 Basics of Image Processing
  • Image acquisition
  • Processing
  • Communication
  • Display
  • Electromagnetic spectrum
  • Elements of visual perception - Structure of the human eye, Image formation in the eye, Brightness adaptation and discrimination, Image formation model, Uniform and non-uniform sampling, Quantization, Image formats.
200 Image Enhancement
  • Spatial domain -
  • Point processing techniques
  • Histogram processing
  • Neighbourhood processing
  • Frequency domain techniques - 2D-DFT
  • Properties of 2D-DFT
  • Low pass
  • High pass
  • Noise removal
  • Homomorphic filter
  • Basics of colour image processing.
300 Image Segmentation
  • Basic relationships between pixels - Neighbours, Adjacency, Connectivity, Regions, Boundaries, Distance measures.
  • Detection of discontinuities, Point, Line
  • Edge detection
  • Edge linking
  • Hough transform
  • Thresholding-based segmentation
  • Region-based segmentation.
400 Image Transforms
  • DFT, FFT, DCT, DST
  • Hadamard, Walsh, Haar, Slant
  • K-L Transforms
  • Basis functions and basis images
  • Introduction to wavelet transform.
500 Image Compression
  • Fundamentals of image compression models
  • Lossless compression - RLE, Huffman, LZW, Arithmetic coding techniques.
  • Lossy compression - IGS coding, Predictive coding, Transform coding, JPEG, JPEG 2000.
600 Morphology, Representation and Description
  • Dilation
  • Erosion
  • Open, Close
  • Hitor-miss
  • Boundary extraction
  • Region filling
  • Thinning and thickening
  • Chain Codes
  • Polygonal approximations
  • Signatures
  • Fourier descriptors
  • Moments.
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