Department of Computer Science and Engineering
CS474/674 Image Processing and Interpretation (Fall 2008)
Meets: TR 2:30 - 3:45 pm (SEM 347)
Instructor:
Dr. George Bebis
- Email:
bebis@cse.unr.edu
- Phone:
(775) 784-6463
- Office : 235 SEM
- Office Hours: MW 1pm -2:30pm or by appointment
Text:
R. Gonzalez and R. Woods Digital Image Processing, 3rd edition, Prentice Hall, 2008. Errata Sheet.
Other Texts:
- W. Pratt, Digital Image Processing, 3rd edition, John Wiley, 2001.
- M. Petrou and P. Bosdogianni, Image Processing: The Fundamentals, John Wiley, 1999.
- A.Jain, Fundamentals of Digital Image Processing , Prentice Hall, 1989.
.
- K. Castleman, Digital Image Processing, Prentice Hall, 1996.
.
- S. Umbaugh, Computer Vision and Image
Processing: A Practical Approach Using CVIPtools, Prentice Hall, 1997.
Prerequisites
CS202 and MATH/STAT 352. If you do not meet the prerequisite requirements for this course, you should see me immediately.
Description/Objectives
Digital image processing is among the fastest growing computer technologies of the 1990s. With increasing computer power, it is now possible to do numerically many tasks that were previously done using analogue techniques. The objective of this course is to provide an introduction to the theory and applications of digital image processing.
Course Outline (tentative)
- Introduction
- Fundamentals
- Image Transforms
- Image Enhancement
- Image Restoration
- Image Compression
- Image Segmentation
- Representation and Description
- Applications
Exams and Assignments
Grading will be based on two exams, homework assignments, and programming
assignments. Specifically, homework problems will be assigned and collected
for grading on a regular basis. Homework solutions will be made available for
each assignment after the submission deadline.There will be 2 exams: a midterm
and a final. The material covered in the exams will be drawn from the lectures
and the homework. Also, there will be several programming assignments which
will be done on an individual basis. For each programming assignment, you are
to turn in a brief report which should include a description of the problem,
a description of your approach, and your evaluation of the results. Details
of the deliverables will be given for each assignment respectively.
Course Policies
Lecture slides, assignments, and other useful information will be posted on
the this web page. Graduate students will be required to do extra work in the
form of extra homework problems, extra exam problems, and a paper presentation
at the end of the semester. Discussion of the programming assignments is
allowed and encouraged. However, each student should do his/her own work.
Assignments which are too similar will receive a zero. No late homework or
programming assignments will be accepted unless there is an extreme emergency.
If you are unable to hand in an assignment by the deadline, you must discuss
it with me before the deadline. Both exams will be closed books, closed notes.
If you are unable to attend an exam you must inform me in advance. No
incomplete grades (INC) will be given in this course and a missed exam may
be made up only if it was missed due to an extreme emergency. Regular
attendance is highly recommended. If you miss a class, you are responsible for
all material covered or assigned in class. You should carefully read the
section on Academic Dishonesty found in the UNR Student Handbook (copies of
this section are available
on-line)) Your continued enrollment in this course implies that you have
read it, and that you subscribe to the principles stated therein.
Disability Statement
Any student with a disability needing academic accomodations is requested
to speak with me or contact the Disability Resource Center (Thompson Building,
Suite 101), as soon as possible to arrange for appropriate accomodations.
Useful Information
- Research
- Important Resources
- 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)
- Useful Mathematics, Statistics, and Geometry resources
- Formats and Viewers
- Software
- CVIPtools: a GUI-based computer vision and image processing tools, ANSI-C source code and librariesfor Windows95/NT and UNIX, extended computer imaging TCL shell. Also contains an extended Tcl shell with all the computer imaging functions. ANSI-C source code and libraries for image analysis, image compression, image enhancement, image restoration, and many imaging utilities.
- Intel Computer Vision Library (OpenCV): image processing and computer vision algorithms optimized to run on Intel microprocessors.
- KHOROS
- Matlab: a numeric computation and visualization environment. The image processing and signal processing toolboxes are especially useful. See also: Matlib Tutorial (Univ Utah), Matlab Basics (RPI), Matlab Primer (200K postscript; 25 pages).
- More software .... (Good stuff !!)
- Source Code for Reading/Writing Images
- Other
- Debugging
Handouts
Lectures
Homework Assignments
Programming Assignments
Presentation Topics (for Graduate Students)
1. Automatic Detection of TV commercials, IEEE Potentials, April/May 2004 (6 pages)
2. Fingerprinting for Security, IEEE Potentials, August/September 2001 (6 pages)
3. Image Compression Techniques, IEEE Potentials, February/March 2001 (5 pages)
4. Watermarking, IEEE Potentials, October/November 2003 (4 pages) (see also this)
5. Multibiometric Systems, Communications of the ACM, January 2004 (7 pages)
6. Biometric Identification, Communications of the ACM, February 2000 (8 pages)
7. Computer Vision in the Interface, Communications of the ACM, January 2004 (7 pages)
Presentation Guidelines
1. Presentations should be professional as if it was presented in a formal confe
rence (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 definit
ions and results are related to each other and to the big picture.
3. You should have your remarks prepared and somewhat memorized. You may use not
es, however if your notes were somehow lost or destroyed you should be able to g
ive your presentation anyway. Reading from your notes excessively will be a very
bad thing...
4. Anticipate Questions: think of the five most likely questions and plan out yo
ur answer Understand the Question: paraphrase it if necessary; repeat it if need
ed. Do Not Digress. Be Honest: if you can't answer the question, say so
5. Each student's material is different but 15 - 20 minutes each should be more than adequate time for your presentation.
6. Meet the eyes of your audience from time to time.
7. Vary the tone of your voice and be careful to speak clearly and not talk too
quickly.
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)
