Department of Computer Science and Engineering
CS474/674 Image Processing and Interpretation (Fall 2023)
Meets: MW 1:00 pm - 2:15 pm (WPEB 200)
Instructor:
Dr. George Bebis
- Email:
bebis@unr.edu
- Phone:
(775) 784-6463
- Office: 411 WPEB
- Office Hours: MW 3:45pm - 4:45pm
TA: Aminul Huq
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.
Digital image processing is among the fastest growing computer technologies. 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.
Course Outline (tentative)
- Introduction
- Intensity & Geometric Transformations
- Spatial Filtering & Convolution
- Fourier Transform & Frequency Domain Filtering
- Sampling and Aliasing
- Image Restoration
- Image Compression
- Short-Time Fourier Transform
- Multi-resolution Representations & 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.
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 need to 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.
Useful Information
- 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)
- Formats and Viewers
- Source Code for Reading/Writing Images
- Other
Handouts
Sample Exams
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)