University of Mumbai Syllabus For Semester 7 (BE Fourth Year) Image Processing: Knowing the Syllabus is very important for the students of Semester 7 (BE Fourth Year). Shaalaa has also provided a list of topics that every student needs to understand.
The University of Mumbai Semester 7 (BE Fourth Year) Image Processing syllabus for the academic year 2022-2023 is based on the Board's guidelines. Students should read the Semester 7 (BE Fourth Year) 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 7 (BE Fourth Year) Image Processing Syllabus pdf 2022-2023. They will also receive a complete practical syllabus for Semester 7 (BE Fourth Year) Image Processing in addition to this.
University of Mumbai Semester 7 (BE Fourth Year) Image Processing Revised Syllabus
University of Mumbai Semester 7 (BE Fourth Year) Image Processing and their Unit wise marks distribution
University of Mumbai Semester 7 (BE Fourth Year) Image Processing Course Structure 2022-2023 With Marking Scheme
| # | Unit/Topic | Weightage |
|---|---|---|
| 100 | Digital Image and Video Fundamentals | |
| 200 | Image Enhancement | |
| 300 | Image Segmentation and Representation | |
| 400 | Image Transform | |
| 500 | Image Compression | |
| 600 | Binary Image Processing | |
| Total | - |
Syllabus
- Introduction to Digital Image, Digital Image Processing System, Sampling and Quantization, Representation of Digital Image, Connectivity
- Image File Formats:- BMP, TIFF and JPEG.
- Colour Models (RGB, HSI, YUV) Introduction to Digital Video, Chroma Sub-sampling, CCIR standards for Digital Video
- Gray Level Transformations
- Zero Memory Point Operations
- Histogram Processing
- Neighbourhood Processing
- Spatial Filtering
- Smoothing and Sharpening Filters
- Homomorphic Filtering
- Detection of Discontinuities, Edge Linking using Hough Transform, Thresholding, Region based Segmentation, Split and Merge Technique, Image Representation and Description, Chain Code, Polygonal Representation, Shape Number, Moments.
- Introduction to Unitary Transform
- Discrete Fourier Transform(DFT), Properties of DFT
- Fast Fourier Transform(FFT)
- Discrete Hadamard Transform(DHT)
- Fast Hadamard Transform(FHT)
- Discrete Cosine Transform(DCT)
- Discrete Wavelet Transform(DWT)
- Introduction, Redundancy, Fidelity Criteria
- Lossless Compression Techniques:- Run Length Coding, Arithmetic Coding, Huffman Coding, Differential PCM
- Lossy Compression Techniques:- Improved Gray Scale Quantization, Vector Quantization, JPEG, MPEG-1.
- Binary Morphological Operators, Hit-or-Miss Transformation, Boundary Extraction, Region Filling, Thinning and Thickening, Connected Component Labeling, Iterative Algorithm and Classical Algorithm.
