Computer Assisted Image Analysis II

As a continuation of Computer Assisted Image Analysis I, this course aims at giving a deeper knowledge of theory and methods in image analysis, and their applications in different realistic scenarios.

• Image analysis pipeline. Analysis of high-dimensional images.
• Experimental design and evaluation techniques.
• Image filtering and restoration.
• Inverse problems in image analysis.
• Advanced methods for image segmentation.
• Registration of images, search methods and optimisation.
• Digital geometry and mathematical morphology.
• Computer vision.
• Classification methods.
• Deep learning for image segmentation and classification.

A number of guest lecturers will present different topics covered in the course. All lectures are given at the IT Department, Polacksbacken, room 2344 (ITC) according to the schedule below.

See here for the schedule.

During the lab sessions, you will have a chance to try out methods which you learned during the lectures. It is beneficial to come prepared! That includes reading the material presented during the lectures, as well as other recommended relevant material (e.g., sections in the textbook). If you come prepared, you can use the time during the lab sessions to get help from lab assistants regarding the tasks you may have difficulties with. You are required to write a lab-report describing your work on the tasks and conclusions drawn.

The three lab sessions will be in room 2315/D (ITC). See labs for times and topics.

During the course, you will work on projects, in teams of 2 students. Teams can propose a topic, or select one of the project topics we have suggested. Each team is required to prepare a project report which will be reviewed by another project team.
During the last session of this course, each team will present and discuss their work to/with the whole group.

See here for more details.

For each lab completed before its deadline you will receive 1 additional point on the exam (the total points at the exam is 40). Check the course page on Studentportalen where we keep track of completed labs.

At the exam you will be allowed to have one sheet (two sides) with hand-written notes. Preparing your own notes for the exam can be a helpful studying technique.

Please look through the examples of previous exams, provided on Studentportalen, to see what type of questions you should expect during the exam.

Lectures notes (slides) in electronic form will be available before the lectures.

Several lectures are based on this book:
M. Sonka, V. Hlavac, and R. Boyle, "Image Processing, Analysis, and Machine Vision", 3rd edition, International Thomson Publishing, 2008. ISBN: 978-0-495-24438-7

You can get it at any bookstore (e.g. LundeQ) and also online, for example at: amazon.co.uk, adlibris.com or bokus.com.

There is also a companion book that complements the textbook. This book is not course literature, but the homepage for the book contains many demos, slides and MATLAB code that may be helpful.

The book used in Computer Assisted Image Analysis I
R. C. Gonzales and R. E. Woods. Digital Image Processing, 4th edition. Pearson, 2018
(or its 3rd edition) contains material relevant for several lectures.