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 2022-2023 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 2022-2023. They will also receive a complete practical syllabus for Semester 6 (TE Third Year) Digital Image Processing in addition to this.
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 2022-2023 With Marking Scheme
| # | Unit/Topic | Weightage |
|---|---|---|
| 100 | Basics of Image Processing | |
| 200 | Image Enhancement | |
| 300 | Image Segmentation | |
| 400 | Image Transforms | |
| 500 | Image Compression | |
| 600 | Morphology, Representation and Description | |
| Total | - |
Syllabus
- 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.
- 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.
- 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.
- DFT, FFT, DCT, DST
- Hadamard, Walsh, Haar, Slant
- K-L Transforms
- Basis functions and basis images
- Introduction to wavelet transform.
- Fundamentals of image compression models
- Lossless compression - RLE, Huffman, LZW, Arithmetic coding techniques.
- Lossy compression - IGS coding, Predictive coding, Transform coding, JPEG, JPEG 2000.
- Dilation
- Erosion
- Open, Close
- Hitor-miss
- Boundary extraction
- Region filling
- Thinning and thickening
- Chain Codes
- Polygonal approximations
- Signatures
- Fourier descriptors
- Moments.
