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.
Bachelor of Computer Science - 132 CRs
Rafael C. Gonzalez , Richard E. Woods, Digital Image Processing, Pearson
content serial | Description |
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1 | Introduction to DIP |
2 | Image histograms |
3 | Image enhancements using transformation |
4 | Spatial filtering |
5 | Morphological image processing part 1 |
6 | Morphological image processing part 2 |
7 | Image segmentation part 1 |
8 | Image segmentation part 2 |
9 | Feature extraction |
10 | Feature extraction and classification part 1 |
11 | Classification part 2 |
12 | Image recognition part 1 |
13 | Image recognition part 2 |
14 | Projects Discussions |
15 | Revision |
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