|title ||Digital Image Processing|
|arbic title |
|prequisites ||CS212, BA201 |
|credit hours ||3|
|Description/Outcomes ||This course emphasizes general principles of image processing, rather than specific applications. It covers topics such as image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, wavelets, noise reduction and restoration, feature extraction and recognition tasks, and image registration.|
|arabic Description/Outcomes |
|objectives ||1. Understand image processing, computer imaging systems, resolution concerns, and image formats.|
2. Illustrate image digitization, image properties, and noise in images.
3. Realize image pre-processing enhancements: pixel brightness transformation, geometric transformations, and local filtering using masks.
4. Apply image segmentation: threshold based, edge-based, region based, and matching.
5. Understand shape representation and description.
6. Apply mathematical morphology
7. Introduce classification and recognition in image analysis
8. Implement a computer program on Matlab or Python to for an image analysis application
9. Present a framework for an image analysis application pipeline
|arabic objectives |
|ref. books ||1. Rafael Gonzalez, Richard Woods, and Steven Eddins, Digital Image Processing using Matlab, Gatermark Publishing.|
2. Chris Solomon & Toby Breckon, Fundamentals of Digital Image Processing: A Practical Approach,Wiley.
|arabic ref. books |
|textbook ||Rafael C. Gonzalez , Richard E. Woods, Digital Image Processing, Pearson.|
|arabic textbook |
|objective set |
|content set |
|course file ||
4_CS455_CS455 - Digital Image Processing.pdf|