Innovations & Experiences in
the Multidisciplinary Course
EGR 4353, Image Formation
& Processing
Jason Gomes
Bo Xu
Zhuocheng Yang
Mentor: Dr. Jim Farison
Abstract
The goal of this presentation is to give an
introduction to the Image Formation and
Processing course offered in Fall 2007.
Description of the course content and
conducting methods will be given, along
with some analysis of the responses of the
students in the class.
Presentation Outline
Introduction
Course Description
I.
II.
I.
II.
III.
IV.
V.
III.
IV.
V.
Learning Methods
Important Dates
Presentation List
Grading
Innovations
Student Response
Conclusion and Recommendations
Questions
Course Description
EGR 4353, Image Formation and
Processing, is an elective course for
electrical and computer engineering,
mechanical engineer, general engineering,
and computer science majors.
 The course offers an introduction to image
formation systems and methods of image
processing through lecturing and
individualized student projects.

Course Description : Learning
Methods



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2 student research projects and classroom
presentations.
MATLAB student project and presentation.
Midterm test and final exam.
Classroom lectures and discussion.
Homework problem assignments.
MATLAB image processing exercises.
Textbook: Digital Image Processing (3rd edition),
Rafael C. Gonzalez and Richard E. Woods,
Prentice Hall, 2008 .
Course Description: Important
Dates

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– Project 1 Assigned.
– Imaging Systems Presentations.
– Mid-term Test.
– Project 2 Assigned.
– Reviewed Literature
Presentations.
Nov. 5
– Project 3 Assigned.
Nov. 28-30– Student Project Presentations.
Dec. 7
– Final Exam.
Aug. 30
Sept. 17-21
Sept. 28
Oct. 3
Oct. 31-Nov. 5
Bo Xu
Presentation Summary
Grading
Innovations
Course Description:
Presentations List
Series One
Image System Hardware
Series Two
Image Processing Research
Series Three
Image Processing Project
Thermal Imaging
A Conceptual Overview of Edge
Detection
Digital Barcode Reading
Obstetric Ultrasound
Image Processing for Suppressing
Ribs in Chest Radiographs
Mage Types. Formats and
Compression
The Hubble Telescope
Image Processing Methods Used
to Improve Explosive Detection
Morphological Image
Processing using MATLAB
Digital Mammography Systems
Tsunami-affected Areas In
Moderate-resolution Satellite
Images
ROI-Based Processing on
Digital Photograph
3d Seismic Imaging and Its
Effects on the Oil & Gas
Industry
Dynamic Monitoring of Bridges
Using A High-speed Coherent
Radar
Comparing Deblurring
Methods using Four Different
Methods
Breaking Ground in
Groundwater Investigation
Visual Cryptography and Fraud
Decorrelations Stretching
Hardware of MRI Scanner
Medical Image Fusion of PET/CT
Edge Detection of Digital
Images
Multi-spectral Scanner on the
Lansats for Remote Sensing
Multispectral Landsat TM Imaging
for Field Discrimination
Impulse Noise Reduction for
Fingerprint Images
Course Description:
Presentations Grading
Presentation Presentation Presentation
One
Two
Three
Proposed subject
1%
1%
1%
Literature resources
1%
NA
NA
Written (or oral) project
progress report
NA
NA
1%
First draft
1%
1%
NA
Written report
5%
6%
13%
Slides
2%
2%
1%
Oral presentation
5%
5%
4%
Total
15%
15%
20%
Course Description: Overall
Grading
Grading Components
Homework assignments
10%
Midterm test
15%
Final exam
25%
Presentation one
15%
Presentation two
15%
Presentation three
20%
Course Description: Innovations
from other courses
One mid-term exam and one final exam.
 Very few homework assignments.
 Company Allusion.

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50% of grade from presentations.

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Class as team investigating a possible
business venture in image
processing/hardware.
Most of the work done outside class.
Lecture Style.
Jason Gomes
Student Response
Conclusion/Recommendations
Questions
Student Response
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
A more thorough assessment sheet was given to the
students on the last day of lecture.
It asked for detailed responses in the following areas:

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PP Visuals – Lecture style evaluation.
Emphasis - Imaging systems vs. Image processing.
Pace/Level – more/less material, faster/slower, simpler/more
advanced.
Homework – opinions on amount assigned.
Testing – 1 or 2 mid-term preference.
Student Presentations – effectiveness.
Company Allusion – opinions on this aspect of the course.
Extremes – best/worst parts of the course.
Other comments.
Student Response:
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PP Visuals
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Emphasis

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Class lectures were power point presentations, with lots of visual
elements.
5/8 were satisfied.
Main complaint was need for variation.
Chapter 1 (hardware systems, basics, 6 class periods) vs. other
chapters (ideas and methods of image processing).
Balanced response. Seemed to match study concentrations of
students.
Pace/level

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4/8 students wanted a faster pace, with more advanced material.
None suggested a slower pace.
Student Response:

Homework
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Very few homework assignments were collected due
to most of the time being spent on the projects.
Class was divided in response. The students who
wanted more homework wanted basic assignments to
help introduce advanced topics in the presentations.
Testing

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One mid-term and a final.
Students were satisfied with this due to presentation
workload and grade percentage.
Student Response:

Presentations

Imaging Systems
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
Imaging Processing Research Literature
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7/8 students said they learned a significant amount from
the first presentation.
5/8 students responded positively.
Drawback to this presentation seemed to be most of the
learning was individual. Topics were too complex to fit into
a short presentation to the class.
Student Investigation


All of the students enjoyed this project.
Only complaint was lack of satisfaction in depth of project
due to limited knowledge of MATLAB/ topics beforehand.
Student Response:

Company Allusion

All of the student liked the idea, but agreed it was not
implemented effectively.
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Suggestions included forum style lectures and group work.
Extremes
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Presentations were the most liked aspect of the
course by 6/8 students.
Least liked aspects varied, only drawback mentioned
twice was setup for the last presentation.
7/8 students said they learned the most from their
research and listening to others’ presentations.
Responses to least effective learning method varied.
Conclusion

Recommendations
More time for MATLAB project.
 Company allusion is a good idea, but needs
to be implemented more effectively.
 Homework assignments used more effectively
– Specifically MATLAB introduction.
 Presentation heavy format was received very
well.

Questions