Innovations

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Innovations Experiences in the
Multidisciplinary Course EGR 4353, Image
Formation Processing

• Jason Gomes
• Bo Xu
• Zhuocheng Yang
• Mentor Dr. Jim Farison

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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.

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Presentation Outline

1. Introduction
2. Course Description
3. Learning Methods
4. Important Dates
5. Presentation List
6. Grading
7. Innovations
8. Student Response
9. Conclusion and Recommendations
10. Questions

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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.

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Course Description Learning Methods

• 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 .

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Course Description Important Dates

• Aug. 30 Project 1 Assigned.
• Sept. 17-21 Imaging Systems Presentations.
• Sept. 28 Mid-term Test.
• Oct. 3 Project 2 Assigned.
• Oct. 31-Nov. 5 Reviewed Literature
  Presentations.
• Nov. 5 Project 3 Assigned.
• Nov. 28-30 Student Project Presentations.
• Dec. 7 Final Exam.

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Bo Xu

• Presentation Summary
• Grading
• Innovations

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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
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Course Description Presentations Grading
Presentation One Presentation Two Presentation 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
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Course Description Overall Grading
Grading Components
Homework assignments 10
Midterm test 15
Final exam 25
Presentation one 15
Presentation two 15
Presentation three 20
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Course Description Innovations from other courses

• One mid-term exam and one final exam.
• Very few homework assignments.
• Company Allusion.
• Class as team investigating a possible business
  venture in image processing/hardware.
• 50 of grade from presentations.
• Most of the work done outside class.
• Lecture Style.

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Jason Gomes

• Student Response
• Conclusion/Recommendations
• Questions

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Student Response

• 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
• 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.

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Student Response

• PP Visuals
• Class lectures were power point presentations,
  with lots of visual elements.
• 5/8 were satisfied.
• Main complaint was need for variation.
• Emphasis
• 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
• 4/8 students wanted a faster pace, with more
  advanced material.
• None suggested a slower pace.

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Student Response

• Homework
• 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
• One mid-term and a final.
• Students were satisfied with this due to
  presentation workload and grade percentage.

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Student Response

• Presentations
• Imaging Systems
• 7/8 students said they learned a significant
  amount from the first presentation.
• Imaging Processing Research Literature
• 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.

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Student Response

• Company Allusion
• All of the student liked the idea, but agreed it
  was not implemented effectively.
• Suggestions included forum style lectures and
  group work.
• Extremes
• 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.

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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.

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Questions