88003 - Image Processing

Learning outcomes

At the end of the course the student will be able to: - describe the basic issues and the principal applications of image processing; - demonstrate a good understanding of the current state-of-the-art image processing methods; - identify, demonstrate and apply his/her knowledge by analyzing image processing problems and recognizing and employing (or proposing) effective solutions; - design and create practical solutions to a range of common image processing problems. The student will also get the basic knowledge on the main algorithms for: - filtering in the spatial and frequency domain; - image segmentation; - object detection and recognition.

Course contents

- Visual perception

- Image formation: geometry and radiometry

- From analog to digital images

- Digital image chain: acquisition, visualization, and processing

- Image processing:

• Geometric operations
• Point operations
• Local operations
• Image segmentation
• Fourier analysis

- Image segmentation

- Feature extraction

- Lab sessions with ImageJ

Readings/Bibliography

–Gonzalez R., Woods R.: “Digital Image Processing”, Third Edition, Pearson Prentice-Hall, 2002

 

Teaching methods

Lectures, lab practice.

In order to attend the training sessions, all students are required prior attendance of e-learning modules 1 and 2 on health and safety in workplaces  

Assessment methods

In the last weeks of the classe students will tackle a real-word problem (compulsory):

• Group project (small groups: 4/5 people)
• Reading scientific paper
• Finding material (bibliography, images, …)
• Understanding and implementation of some algorithms
• Presentation (both written report and oral presentation) of the project and its outcomes

Final examination: discussion of the group project and oral interview.

Teaching tools

Software for image processing: ImageJ.

Office hours

See the website of Nico Lanconelli