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Computer assisted image analysis I

1TD396, Fall 2018, 5 credits

Goal

  • To give an introduction to the processing and analysis of digital images.

Contents

Representation of images in computers. Image types. Sampling. Image coding and compression. Image processing and image restoration. Point operators. Fundamentals of frequency analysis. Histogram operations. Neighbourhood operators. Mathematical morphology. Segmentation. Shape analysis and feature extraction. Classification and decision theory. Introduction to deep learning. Examples of applications from research and industry.

Information about the re-exam on June 18 2020

The re-exam will be given remotely. The exam itself will be uploaded to the student portal, available to all students registered for the exam during the time scheduled for the exam. Your answers should also be uploaded to the student portal during the scheduled time for the exam.

Since this is a remote exam, the format will be different from previous exams given on the course. This will be an "open book" exam, meaning that you are allowed to use any resources that you want to solve the exam (course literature, lab instructions, etc.). Collaboration between students, however, is NOT allowed. You must solve the exam questions yourself.

Lectures and Labs

Date Time Place Title Teacher Chapters Files
5/11 10:15-12:00 1111, ITC L1: Introduction Filip Malmberg 1, 2.1-2.4 L1.pdf
6/11 8:15-10:00 2347, ITC L2: Pointwise Operators Filip Malmberg 2.6-2.6.4,3.1-3.3 L2.pdf
8/11 8:15-12:00 2510 & 2507 & 1549, ITC LAB 1 Elisabeth Wetzer, Axel Andersson lab1.zip
12/11 10:15-12:00 2347, ITC L3: Filtering 1 Filip Malmberg 2.5.1-2.5.2, 3.4-3.7, 5.3, 9.1-9.3 L3.pdf
13/11 10:15-12:00 Häggsalen, 10132, Ångström L4: Filtering 2 Filip Malmberg 4.2-4.10, 4.11.1, 4.11.3, 5.4 L4.pdf
14/11 8:15-12:00 2510 & 2507& 1412 ,ITC LAB 2 Elisabeth Wetzer, Nadezhda Koriakina, Axel Andersson, Ankit Gupta lab2.zip
15/11 8:15-10:00 Häggsalen 10132, Ångström L5: Image Segmentation Filip Malmberg 10.1, 10.3,10.5, 9.1-9,3 L5.pdf
19/11 10:15-12:00 1111, ITC L6: Classification Natasa Sladoje 12 L6.pdf
20/11 15:15-17:00 2247, ITC L7: Object description Robin Strand 11.1-11.4 L7.pdf
21/11 8:15-12:00 2510 & 2507 & 1549, ITC LAB 3 Elisabeth Wetzer, Nadezhda Koriakina, Axel Andersson, Ankit Gupta lab3.zip
28/11 10:15-12:00 2347, ITC L8: Deep Learning for Image Analysis Joakim Lindblad L8.pdf
3/12 8:15-12:00 2510 & 1515, ITC LAB 4 Elisabeth Wetzer, Nadezhda Koriakina, Axel Andersson, Eva Breznik Ankit Gupta lab4.zip
5/12 10:15-12:00 2247, ITC L9: Color Images and Image Compression Filip Malmberg 6,8 L9.pdf
10/12 10:15-12:00 2347, ITC L10: Summary, old exams (CANCELLED) Filip Malmberg OldExam.pdf
13/12 13:15-17:00 1412& 2510 & 2507, ITC LAB 5 Elisabeth Wetzer, Nadezhda Koriakina, Axel Andersson, Eva Breznik lab5.zip
9/1 Lab 5 deadline
9/1 8:00-17:00 EXAM

Labs

During the lab sessions, you will be able to try out things learned in the lectures. Please come prepared! That means, go over the lectures again and read the relevant sections in the book. If you are properly prepared, you should be able to finish all the exercises during the lab session.

Literature

Most of the lectures are based on this book:

  • R. C. Gonzalez and R. E. Woods, "Digital Image Processing",3rd. ed. : Upper Saddle River, N.J. : Prentice Hall, cop. 2008, ISBN: 978013505267-9.

You can get it (or order it) at e.g. Studentbokhandeln AB here in Uppsala or online, for example at: adlibris.com or bokus.com. A few books are also available through libraries.

Copies of slides and other material will be handed out during most of the lectures. The written exam is based on content covered in the lectures (oral presentation, lecture notes and blackboard examples). The book is highly recommended for background information and details about methods and theory.

Uppdaterad  2020-06-16 16:00:44 av Filip Malmberg.