Fall 2013 Undergraduate Elective
(EENG 4010)-Section 001: Computer Vision
&
Fall 2013 Graduate Course: Computer Vision and Image Analysis (EENG 5640)- Section 001
Instructor:
Parthasarathy (Partha)
Guturu
Faculty Office: UNT
Discovery Park B-235
Phone: 940-891-6877
Email: guturu@unt.edu
Teaching
Assistant: TBD
Class Hours:
M/W 4:00 PM - 5:20 PM.
Classroom: UNT
Discovery Park B-217.
Office Hours:
T 2:00 PM-3:30 PM. Students unable to see me during this time may request an
appointment.
Prerequisite: Senior
standing (for undergraduates)
Course
Description
This advanced elective course is designed to introduce to the senior undergraduate students mathematical principles of computer vision. Binary image processing with techniques of mathematical morphology, grey level image processing with various filters, color fundamentals and texture representation and recognition will be discussed. Advanced topics such as content based image retrieval, shape form X-techniques, 2D/3D object recognition and matching will also be discussed. A programming project on one of the topics will be included in this course.
Course
Delivery Plan
|
Topic No. |
Topic |
Time
Allocated |
|
1. |
Image Formation, Representation, basics of image processing,
pattern recognition, and Computer
Vision |
1 Week |
|
2. |
Binary Image Analysis and Mathematical
Morphology |
1 Week |
|
3. |
Grey Level Image Processing- Filtering,
Enhancement and Edge Detection |
1 Week |
|
4. |
Image Segmentation and Representation |
1 Week |
|
5. |
Color and Shading |
1 Week |
|
6. |
Texture |
1 Week |
|
7. |
Content-based Image
Retrieval |
1 Week |
|
8. |
2D Matching |
1 Week |
|
9. |
Shape from X ( =
shading/texture/motion/stereo/boundary) |
3 Weeks |
|
10. |
3D Object Recognition |
1 Week |
Reading
Requirements
Students are
required to come prepared to every class with the material discussed in the
previous class.
Reference Book:
1. Computer Vision by Linda G Shapiro, and George Stockman Publisher: Prentice
Hall; 1st edition (January 23, 2001) Language: English ISBN-10: 0130307963
ISBN-13: 978-0130307965.
Attendance
Policy: In
view of the continuous evaluation strategy adopted by the instructor, perfect attendance
is recommended for those aspiring to get good grades.
Grading
Policy: The
undergraduate students will have a totally different set of examinations with
emphasis on problem solving rather than theory and algorithms, vis-a-vis the graduate students. The break-up for overall
grading is as follows.
Assignments/Quizzes/Class
Tests: 50, Project: 30, and Final Examination: 20. Grades A, B, C, D, and F
will be assigned, respectively, depending upon whether the total tally will be
greater than/equal to 90, 80-89, 70-79, 60-69, or less than 60.
Academic
Dishonesty: Honesty is the best policy.
Cheating will not be tolerated. Anyone found guilty of cheating on a test or
assignment will be awarded an F grade for the course. Discussions of problems
and assignment with your classmates is welcome and encouraged, however, sharing
of solutions is not. If you need help, you should ask the instructor. Cheating
includes, but is not limited to, all forms of plagiarism and misrepresentation.
For your rights and responsibilities please refer to http://www.unt.edu/csrr
Statement
regarding Disabled Students: The Faculty of Electrical
Engineering including this instructor cooperates with the Office of Disability
Accommodation (ODA) to make reasonable accommodations for students with
certified disabilities (cf. Americans with Disabilities Act and Section 504,
Rehabilitation Act). If you have not registered with ODA, we encourage you to
do so immediately and present a written accommodation request along with an
appropriate documentation from the Dean of Students Office http://www.unt.edu/oda/, on or before the 2nd
week of class.
Final Exam Date and Time: TBD.
Course Learning Outcomes
Course
Learning Outcomes (CLOs) for Advanced Topics in Electrical Engineering-
Computer Vision (EENG-4010) are as follows:
[CLO-1]
Basics
of image processing, pattern
recognition, and computer vision
[CLO-2]
Binary
Image Analysis and Mathematical Morphology
[CLO-3]
Grey
Level Image Processing- histogram methods, filters, edge detection
[CLO-4]
Image
segmentation, shape representation and recognition
[CLO-5]
Color
fundamentals
[CLO-6]
Texture
representation and recognition
[CLO-7]
Content-based
image retrieval
[CLO-8]
2D-Matching
with affine transforms
[CLO-9]
Shape
from X-techniques (binocular/photometric stereo, motion, etc.)
[CLO-10]
3D-representations
and object recognition with applications
[CLO-11]
Computer
Vision Project Design, Implementation and Reporting
Student Outcomes (SOs)of Our
BSEE Program
Upon completion of our BSEE
program, the students will be able to:
[SO-1] Apply knowledge of mathematics, engineering and science.
[SO-2] Design and conduct experiments to verify and validate the design projects developed by them, and analyze and interpret data.
[SO-3] Develop project-based learning skills through design and implementation of a system, component, or process that meets the needs within realistic constraints.
[SO-4] Function on multidisciplinary teams.
[SO-5] Identify, formulate, and solve engineering problems.
[SO-6] Have an understanding of professional and ethical responsibility.
[SO-7] Communicate effectively.
[SO-8] Achieve broad education necessary to understand the impact of electrical engineering solutions in a global and societal context.
[SO-9] Understand learning
processes, concepts of learning to learn, and engage in lifelong learning.
[SO-10] Achieve knowledge of contemporary issues.
[SO-11] Use techniques, skills, and computer-based tools for conducting experiments and carrying out designs.
ABET Outcomes
3a- an ability to apply knowledge of mathematics, science, and engineering
3b- an ability to design and conduct experiments, as well as to analyze and interpret data
3c- an ability to design a system, component, or process to meet desired needs
3d- an ability to function on multi-disciplinary teams
3e- an ability to identify, formulate, and solve engineering problems
3f- an understanding of professional and ethical responsibility
3g- an ability to communicate effectively
3h- the broad education necessary to understand the impact of engineering solutions in a global and societal context
3i- a recognition of the need for, and an ability to engage in life-long learning
3j- a knowledge of contemporary issues
3k- an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
Relationship
of the course to Student Outcomes (SOs)
|
CLO |
Program Outcomes/ABET Outcomes |
||||||||||
|
|
SO-1/
3(a) |
SO-2/
3(b) |
SO-3/
3I |
SO-4/
3(d) |
SO-5/
3(e) |
SO-6/
3(f) |
SO-7/
3(g) |
SO-8/
3(h) |
SO-9/
3(i) |
SO-10/
3(j) |
SO-11/
3(k) |
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