Digital Image Processing

The objective of this undergrad course is to present the mathematical techniques used in the manipulation, filtering, restoration, segmentation and representation of digital images. The student will become capable of choosing the techniques more suited to tackling specific tasks. In addition, the practical lectures will aim at developing new digital image processing algorithms using experiments.

Course summary

1. Introduction.
2. Image fundamentals.
3. Intensity transformations and spatial filtering.
4. Filtering in the frequency domain.
5. Restoration.
6. Color processing.
7. Morphology.
8. Segmentation.

Methodology

Presentation of mathematical theory with;

• presentation slides;
• practice classes in the Image Processing Lab, and;
• development of projects aimed at solving specific tasks.

Grading

The grades are comprised by the following activities. Homework (HW), practical exam (PE) and project (P). The total amount corresponds to one grade per two months.

HW (30%) + PE (35%) + PJ (35%) = AB (100%).

Target publications

Journals

• IEEE Trans. Image Processing.
• IEEE Trans. Medical Imaging.
• IEE Proceedings. Vision, Image and Signal Processing.
• IET Computer Vision.
• Image and Vision Computing.

Conference

• ICIP IEEE International Conference on Image Processing A1
• MICCAI International Conference on Medical Image Computing and Computer Assisted Intervention A1
• CAIP International Conference on Computer Analysis of Images and Patterns B1
• ICIAP International Conference on Image Analysis and Processing B1
• ICIAR International Conference on Image Analysis and Recognition B1
• IWSSIP International Conference on Systems, Signals and Image Processing B1
• SIBGRAPI Conference on Graphics, Patterns and Images B1
• VCIP IEEE International Conference on Visual Communications and Image Processing B1

Links

• Review material (Gonzales).
• Tutorial on Matrix Manipulation (Gonzales - MATLAB).
• MATLAB Array Manipulation Tips and Tricks (Gonzalez).
• Source code (DIPUM - MATLAB).
• Images (DIPUM).
• Matlab (Mathworks).
• OpenCV.
• ImageJ.
• GIMP.

Projects

The project proposal is due XX, 2017.

The proposal must contain:

• Title.
• Authors.
• Objectives.
• Justification (max. 2 paragraphs or 10 lines).
• Methodology.
• Execution time schedule.
• References.

Project report:

• The project report must use the IEEE Latex template. Final reports will be accepted only in this format!

The project must comprise 5 stages:

1. Problem description. Technique used to tackle the problem - methodology.
2. How the technique was implemented.
3. Technique assessment using experiments.
4. Analysis of results.
5. Conclusion presenting an overview of the project and assessing what was realized and learned.

Links

Matlab.

OpenCV.

ImageJ.

GIMP.

References

• Gonzalez, Rafael C.; Woods, Richard E. "Digital Image Processing", 3a Ed., Pearson.
• Gonzalez , Rafael C.; Woods, Richard E.; Eddins, Steven L.; “Digital Image Processing Using MATLAB”, 2a Ed., Gatesmark Publishing.