CS 586-3
Pattern Recognition and Image Processing
Catalog Description
An introduction to the area of computer vision for the purpose of restoration, segmentation, encoding, analysis, and recognition of pictures. Topics include: image transforms, edge detection, smoothing, filtering, pseudo-coloring, syntactic methods in scene analysis, parametric decision theory, non-parametric decision theory, linear discriminant functions, parameter estimation, supervised learning, and unsupervised learning.
Prerequisite:
CS 220 and Math 380 or consent of instructor.
Course Outline
| Lectures | ||
| 1. | Computer Representation and Display of Picture Data | 3 |
| 2. | Image Transforms (FFT) | 7 |
| 3. | Image Enhancement | 3 |
| 4. | Image Encoding | 3 |
| 5. | Descriptive Methods in Scene Analysis | 2 |
| 6. | Restoration . | 4 |
| 7. | Non Parametric Decision Theory | 4 |
| 8. | Linear Discriminant Functions | 3 |
| 9. | Statistical Discriminant Functions | 6 |
| 10. | Clustering and Non Supervised Learning | 5 |
| Total | 40 | |