Computer Science Department

The University of Western Ontario
London, Canada

CS 4487/9587A --- Algorithms for Image Analysis

Syllabus: Fall 2015

General Description

This course has two components. On the one hand, it is an introduction to digital image analysis presenting selected fundamental problems in computer vision, medical image analysis, photo/video editing, and graphics. We cover such basic concepts as image segmentation, registration, object recognition/matching, tracking, texture, etc. On the other hand, this is an applied course on standard computer science algorithms where students develop practical understanding of dynamic programming, graph-based algorithms, clustering methods, etc. In fact, image analysis provides a stimulating environment for studying algorithms as their outputs can be intuitively visualized. Students with previous background in algorithms will be exposed to applications in image analysis, while students already familiar with problems in imaging will learn efficient methods based on standard CS algorithms. The course emphasizes the design, analysis, and implementation of algorithms in the context of 2D/3D medical images, photo and video data.

Lectures: Monday 1:30 - 3:30pm at AHB-1B04
Wednesday 2:30 - 3:30pm at NCB-117

Instructor Information

Instructor: Prof. Yuri Boykov
Office: Middlesex College 387
Office Hours : after class or by appointment
E-Mail: yuri 'at'
Phone: (519) 661-2159 (UWO office)
(226) 289-6980 (UWO vision lab)


Note: Students are responsible for ensuring that they have either the prerequisites for this course, or written special permission from the instructor. If a student does not have the course prerequisites, and has not been granted a special permission, it is in his/her best interest to drop the course well before the end of the add/drop period. If a student is not eligible for a course, he/she may be removed from it at any time, and will receive no adjustment to his/her fees. These decisions can not be appealed. Lack of prerequisites may not be used as the basis of appeal.

Course Website

The website for the course is Lecture notes, assignments, code samples, and other supplementary materials will be posted on this web site. Many important announcements will be posted as well. It is your responsibility to check this web site on a regular basis. OWL will be used primarily for collecting homework assignments and projects.

Textbooks and Lecture Notes

There is no required textbook for this course. All lecture notes/slides will be available on the course web site. While the posted slides cover all the necessary material, they are supposed to be complemented by live discussion and blackboard scribbles. Note that class attensdance is very important since the posted slides are not designed for independent reading. Lecture notes could be complemented by readings from recommended text-books on computer vision and standard CS algorithms given below. You will be referred to specific relevant sections of these books in class.

Course Content

This course presents many standard computer vision problems and their solution methods using common algorithms (e.g. dynamic programming, shortest paths, graph cuts, minimum ratio cycle). The studied image analysis problems provide an intuitive visual environment helping better understanding of such optimization methods. A tentative list of topics is given below.


There will be homework assignments based on programming projects.


There will be 3 short surprise quizzes given at the beginning of classes every 3-4 weeks. Your 2 best results (out of 3) will be used in the grading scheme. No make-ups will be offered.

Final Exam

There will be no exams in this course.

Grading Scheme

Homework assignments will include some additional parts for graduate students. These parts will be optional (extra credit) for undergraduates taking this course (CS4487). Mini project is required for graduate students only, however undergraduate students enthusiastic about stereo probem can obtain up to 30% extra credit for the project (partial credit is possible).
CS4487 (undergrads) CS9587 (grad. students)
Quizzes 10% 10% (5% each for 2 best out of 3)
Assignments 30% + 30% + 30% 20% + 20% + 20%
Mini Project 0% (extra credit is possible) 30%

Best Ways to Contact me

If you have a question and need to contact me, the best way to do so is to talk to me right after class. You can also email me to make an appointment. All emails should be sent from your UWO account and they should have CS4487/9587 in the subject line. Otherwise your email is likely to get filtered out.

Academic Accommodation for Medical Illness

If you are unable to meet a course requirement due to illness or other serious circumstances, you must provide valid medical or supporting documentation to the Academic Counselling Office of your home faculty as soon as possible. If you are a Science student, the Academic Counselling Office of the Faculty of Science is located in WSC 140, and can be contacted at 519-661-3040 or Their website is

A student requiring academic accommodation due to illness must use the Student Medical Certificate ( when visiting an off-campus medical facility.

For further information, please consult the university’s medical illness policy at

Accomodations for properly documented medical illness would be determined on a case-by-case basis. Typically, that could be a deadline extension.

Support Services

Learning-skills counsellors at the Student Development Centre ( are ready to help you improve your learning skills. They offer presentations on strategies for improving time management, multiple-choice exam preparation/writing, textbook reading, and more. Individual support is offered throughout the Fall/Winter terms in the drop-in Learning Help Centre, and year-round through individual counselling.

Students who are in emotional/mental distress should refer to Mental Health@Western ( for a complete list of options about how to obtain help.

Additional student-run support services are offered by the USC,

The website for Registrarial Services is

Code of Student Conduct

To foster a supportive and enriching academic environment that is conducive to learning and free inquiry, Western has a Code of Student Conduct (