Image Processing — Student Assignments and Projects
Owner-approved assignments and projects prepared by students in the Image Processing course.
Browse the organized Student Works in the Jupyter Book for section navigation and detailed projects.
Section 3
RGB Color Segmentation Using Dominant Channels and Histogram Peaks
A student image-processing project documenting RGB color segmentation with channel-dominance masks, Gaussian-smoothed histograms, adaptive peak intervals, and morphological post-processing. The report also compares the RGB approach conceptually with HSV segmentation. The uploaded archive contains LaTeX documentation; any locally supplied figures will be displayed as submitted, not represented as independently reproduced results.
Read the full project description
دانشجو:
نیمسال:
- Source files — Part 1 of 2 (ZIP) (44.0 MB) — Download all parts and run RESTORE_LARGE_FILES.py if any original file was split.
- Source files — Part 2 of 2 (ZIP) (35.4 MB) — Download all parts and run RESTORE_LARGE_FILES.py if any original file was split.
- main (4.0 MB) — PDF supplied with the project
Low-Rank Approximation of 2-D Convolution Filters Using SVD
This student project studies how singular value decomposition (SVD) can approximate a non-separable 2-D convolution kernel with lower-rank separable filters. The package includes a Persian report, Python implementation, numerical results, and example figures comparing full filtering with rank-1, rank-2, and rank-4 approximations. It is directly relevant to image processing topics such as spatial filtering, separability, computational efficiency, and approximation error.
Read the full project description
دانشجو:
نیمسال:
- Project source package (ZIP) (915.8 KB) — Converted ZIP package containing the original project files, report source, Python code, numerical outputs, and figures.
- Persian project report (PDF) (534.9 KB) — Main Persian report explaining SVD, low-rank approximation, separable convolution, implementation details, and discussion.
- Filtered output comparison figure (PDF) (328.1 KB) — Example figure comparing the original filtered image with rank-1, rank-2, and rank-4 approximations.