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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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Presentation on theme: "Innovations & Experiences in the Multidisciplinary Course EGR 4353, Image Formation & Processing Jason Gomes Bo Xu Zhuocheng Yang Mentor: Dr. Jim Farison."— Presentation transcript:

1 Innovations & Experiences in the Multidisciplinary Course EGR 4353, Image Formation & Processing Jason Gomes Bo Xu Zhuocheng Yang Mentor: Dr. Jim Farison

2 Abstract The goal of this presentation is to give an introduction to the Image Formation and Processing course offered in Fall Description of the course content and conducting methods will be given, along with some analysis of the responses of the students in the class. The goal of this presentation is to give an introduction to the Image Formation and Processing course offered in Fall Description of the course content and conducting methods will be given, along with some analysis of the responses of the students in the class.

3 Presentation Outline I. Introduction II. Course Description I. Learning Methods II. Important Dates III. Presentation List IV. Grading V. Innovations III. Student Response IV. Conclusion and Recommendations V. Questions

4 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. 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. The course offers an introduction to image formation systems and methods of image processing through lecturing and individualized student projects.

5 Course Description : Learning Methods 2 student research projects and classroom presentations. 2 student research projects and classroom presentations. MATLAB student project and presentation. MATLAB student project and presentation. Midterm test and final exam. Midterm test and final exam. Classroom lectures and discussion. Classroom lectures and discussion. Homework problem assignments. Homework problem assignments. MATLAB image processing exercises. MATLAB image processing exercises. Textbook: Digital Image Processing (3rd edition), Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, Textbook: Digital Image Processing (3rd edition), Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, 2008.

6 Course Description: Important Dates Aug. 30 – Project 1 Assigned. Aug. 30 – Project 1 Assigned. Sept – Imaging Systems Presentations. Sept – Imaging Systems Presentations. Sept. 28– Mid-term Test. Sept. 28– Mid-term Test. Oct. 3– Project 2 Assigned. Oct. 3– Project 2 Assigned. Oct. 31-Nov. 5– Reviewed Literature Presentations. Oct. 31-Nov. 5– Reviewed Literature Presentations. Nov. 5 – Project 3 Assigned. Nov. 5 – Project 3 Assigned. Nov – Student Project Presentations. Nov – Student Project Presentations. Dec. 7– Final Exam. Dec. 7– Final Exam.

7 Bo Xu Presentation Summary GradingInnovations

8 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 List

9 Presentation One Presentation Two Presentation Three Proposed subject 1%1%1% Literature resources 1%NANA Written (or oral) project progress report NANA1% First draft 1% 1%1%NA Written report 5%6%13% Slides2%2%1% Oral presentation 5% 5%5%4% Total15% 15% 15% 20% 20% Course Description: Presentations Grading

10 Grading Components Homework assignments 10% Midterm test 15% Final exam 25% Presentation one 15% Presentation two 15% Presentation three 20% Course Description: Overall Grading

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

12 Jason Gomes Student Response Conclusion/RecommendationsQuestions

13 A more thorough assessment sheet was given to the students on the last day of lecture. 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: It asked for detailed responses in the following areas: PP Visuals – Lecture style evaluation. PP Visuals – Lecture style evaluation. Emphasis - Imaging systems vs. Image processing. Emphasis - Imaging systems vs. Image processing. Pace/Level – more/less material, faster/slower, simpler/more advanced. Pace/Level – more/less material, faster/slower, simpler/more advanced. Homework – opinions on amount assigned. Homework – opinions on amount assigned. Testing – 1 or 2 mid-term preference. Testing – 1 or 2 mid-term preference. Student Presentations – effectiveness. Student Presentations – effectiveness. Company Allusion – opinions on this aspect of the course. Company Allusion – opinions on this aspect of the course. Extremes – best/worst parts of the course. Extremes – best/worst parts of the course. Other comments. Other comments.

14 Student Response: PP Visuals PP Visuals Class lectures were power point presentations, with lots of visual elements. Class lectures were power point presentations, with lots of visual elements. 5/8 were satisfied. 5/8 were satisfied. Main complaint was need for variation. Main complaint was need for variation. Emphasis Emphasis Chapter 1 (hardware systems, basics, 6 class periods) vs. other chapters (ideas and methods of image processing). 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. Balanced response. Seemed to match study concentrations of students. Pace/level Pace/level 4/8 students wanted a faster pace, with more advanced material. 4/8 students wanted a faster pace, with more advanced material. None suggested a slower pace. None suggested a slower pace.

15 Student Response: Homework Homework Very few homework assignments were collected due to most of the time being spent on the projects. 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. Class was divided in response. The students who wanted more homework wanted basic assignments to help introduce advanced topics in the presentations. Testing Testing One mid-term and a final. One mid-term and a final. Students were satisfied with this due to presentation workload and grade percentage. Students were satisfied with this due to presentation workload and grade percentage.

16 Student Response: Presentations Presentations Imaging Systems Imaging Systems 7/8 students said they learned a significant amount from the first presentation. 7/8 students said they learned a significant amount from the first presentation. Imaging Processing Research Literature Imaging Processing Research Literature 5/8 students responded positively. 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. 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 Student Investigation All of the students enjoyed this project. 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. Only complaint was lack of satisfaction in depth of project due to limited knowledge of MATLAB/ topics beforehand.

17 Student Response: Company Allusion Company Allusion All of the student liked the idea, but agreed it was not implemented effectively. All of the student liked the idea, but agreed it was not implemented effectively. Suggestions included forum style lectures and group work. Suggestions included forum style lectures and group work. Extremes Extremes Presentations were the most liked aspect of the course by 6/8 students. 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. 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. 7/8 students said they learned the most from their research and listening to others’ presentations. Responses to least effective learning method varied. Responses to least effective learning method varied.

18 Conclusion Recommendations Recommendations More time for MATLAB project. More time for MATLAB project. Company allusion is a good idea, but needs to be implemented more effectively. Company allusion is a good idea, but needs to be implemented more effectively. Homework assignments used more effectively – Specifically MATLAB introduction. Homework assignments used more effectively – Specifically MATLAB introduction. Presentation heavy format was received very well. Presentation heavy format was received very well.

19 Questions


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