Department of Computer Science and Engineering
CS474/674 Image Processing and Interpretation (Fall 2026)
Meets: MW 1:00 pm - 2:15 pm (WPEB 200)
Instructor:
Dr. George Bebis
- Email:
bebis@unr.edu
- Phone:
(775) 784-6463
- Office: WPEB 411
- Office Hours: MW 2:30pm - 3:30pm or by appointment
Required Text:
R. Gonzalez and R. Woods Digital Image Processing, 4th edition, Pearson, 2018. Errata
Optional Texts:
- M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, Cengage Learning, 2015.
- S. Birchfield, Image Processing and Analysis, Cengage Learning, 2018.
.
- S. Umbaugh, Digital Image Processing and Analysis, CRC Press, 2011
Prerequisites
CS202 with "C" or better; STAT 352 or STAT 461.
Course Outline (tentative)
This course will provide an introduction to the theory and applications of digital image processing. In particular, this course will introduce students to the fundamental techniques and algorithms used for processing and extracting useful information from digital images.
- Introduction
- Intensity & Geometric Transformations
- Spatial Filtering & Convolution
- Fourier Transform
- Frequency Domain Filtering
- Sampling and Aliasing
- Image Restoration
- Image Compression
- Wavelets (if time permits)
Exams and Assignments
Grading will be based on quizzes, exams, and programming assignments. Graduate students will also need to present a paper.
There will be 7 quizzes during the semester which will be announced at least one class period in advance. The lowest quiz grade will be dropped.
There will be 2 exams: a midterm and a final. The material covered in the exams will be drawn from the lectures and the quizzes.
There will be 3-4 programming assignments which must be done individually.
Graduate students will be required to present a paper to the rest of the class. Each presentation should be 15-20 minutes long and presented in a professional manner (i.e., slides/projector).
Course Policies
Lecture slides, assignments, and other useful information will be posted on the course's web page.
Quizzes and exams will be closed books, closed notes. If you are unable to take a quiz or exam at the designated date and time, you must inform me in advance. Quizzes and exams cannot be made up unless there is an extreme emergency.
Programming assignments must be submitted on Canvas.
Discussion of your work with others is allowed and encouraged. However, each student should do his/her own work. Assignments which are too similar will receive a zero.
No late work will be accepted unless there is an extreme emergency. If you are unable to hand in your work by the deadline, you must discuss it with me before the deadline.
No incomplete grades (INC) will be given on this course and a missed exam may be made up only if it was missed due to an extreme emergency.
Students are expected to attend all lectures and be on time. Students who miss a class and/or are late for a class may experience an impact on their grade by missing course activities. If you miss a lecture, you are responsible for all material covered or assigned.
The instructor reserves the right to add to, and/or modify any of the above policies as needed to maintain an appropriate and effective educational atmosphere. If this happens, all students will be notified in advance of implementation of the new and/or modified policy.
Major IP and CV Journals
Major IP and CV Conferences
- IEEE International Conference on Computer Vision (ICCV)
- IEEE International Conference of Image Processing (ICIP)
- IEEE Computer Vision and Pattern Recognition (CVPR)
- International Conference of Pattern Recognition (ICPR)
Sample code for Read/Write images
Display Images
- Irfanview (freeware graphic viewer for Windows)
Useful Resources
Handouts
Sample Exams
- Midterm Exam (skip the 4th T/F question and problem #4)
- Final Exam (also look the 4th T/F question and problem #4 from the sample Midterm exam)
Lectures
Programming Assignments
Sample Presentation Topics (Graduate Students Only)
Presentation Guidelines
1. Presentations should be professional as if it was presented in a formal conference (i.e., powerpoint slides/projector).
2. Your goal is to educate and inform your audience. Make sure your presentation follows a logical sequence. Help the audience understand how successive definitions and results are related to each other and to the big picture.
3. You should have your remarks prepared and somewhat memorized. Reading from your notes excessively should be avoided.
4. Anticipate Questions: think of some likely questions and plan out your answer. Understand the Question: paraphrase it if necessary; repeat it if needed. Do Not Digress. Be Honest: if you can't answer the question, say so.
5. Meet the eyes of your audience from time to time.
6. Vary the tone of your voice and be careful to speak clearly and not talk too quickly.
7. Each student's material is different but 15 minutes each should be enough time for your presentation.
Department of Computer Science and Engineering, University of Nevada, Ren
o, NV 89557
Page created and maintained by:
Dr. George Bebis
(bebis@cse.unr.edu)