ECE 438 Image Analysis & Computer Vision

Course Syllabus


Professor: Dr. Scott E Umbaugh Office: Engineering Building, Room EB3037

Phone: 650-2524, 2948 e-mail:

Textbook: DIPA: Computer Vision and Image Analysis4th Edition,  Scott E Umbaugh, CRC Press, Taylor & Francis Group, Boca Raton, FL, 2023; Supplementary documents are available at the publisher’s web site as Support Material

Prerequisite: ECE 351 and programming experience, or consent of instructor

Class Format: Two lectures and 1 lab per week, two tests, term project

Web Site Imaging Examples: CVIPtools Imaging Examples , Computer Vision Example Applications

Goals and Objectives: To introduce the student to computer vision algorithms, methods and concepts which will enable the student to implement computer vision systems with emphasis on applications and problem solving. Lab exercises will familiarize the student with typical hardware as well as software development tools. Students will use the C programming language or M-files in Matlab to implement computer vision algorithms.


  • Introduction and Image Sensing 4 Lectures
  • Image Analysis 4 Lectures
  • Edge/Line Detection 4 Lectures
  • TEST #1
  • Segmentation/Morphological Filtering 4 Lectures
  • Fourier Transform 2 Lectures
  • Feature Extraction/Analysis 4 Lectures
  • Pattern Classification 2 Lectures
  • TEST #2
  • PROJECT DUE -- 16th week

Project will be some application of computer vision to digital image(s). Typical projects are simple pattern classification  applications using CVIPtools libraries.

GRADING: Test #1 - 25%, Test #2 - 25%, Lab Exercises - 25%, Project - 25%

HOMEWORK is not collected, but it is highly recommended to work through the problems, as many test problems are based on the homework. The Solutions Manual is available below with the lecture slides.







Overview, computer imaging systems, lenses

Chapter 1

Chap 1: 1-14

suppl: 1,4


Image formation and sensing, CVIPtools, CVIPlab

Chapter 1

Chapter 2

Chap 1: 16-18,24,27,29; suppl: 2,7

Lab: Intro CVIPlab


Image analysis, preprocessing

Chapter 3

Chap 3: 1,2,3,6,9,10,12,13,15,21

Lab: Image Geometry, parts 1-3


Binary image analysis


Chapter 3

Chap 3: 23-28, suppl: 1,2

Lab: Binary Object Features, parts 1,2


Edge, Line, Shape detection

Chapter 4


Labs Due


Edge detection performance, Hough transform, corner/shape detection

Chapter 4

Chap 4: 17-21, suppl:1,2,3,11

Lab: Edge Detection-Roberts&Sobel


Review and TEST #1, Study Guide, Sample test, Sample test KEY





Chapter 5

Chap 5: 1-8


Morphological filtering

Chapter 5

Chap 5: 9,10,11


Lab: Morphological Filters


Segmentation evaluation methods, Intro Feature extraction, shape, histogram, color

Chapter 5&6

Chap 5 suppl: 4,5,6

Chap 6: 1-6,8

Labs Due


Fourier transform, Feature extraction, spectral, texture, using CVIPtools

Project proposal due

Must be approved by Professor

Chapter 6

Chap 6: 11-17,

Suppl: 1,4,5



Feature analysis, feature vectors, distance /similarity measures, data preprocessing

Chapter 6

Chapter 7

Chap 6:18-21

Chap 7: 1-7



Pattern classification

Chapter 7

Chap 7:8-11

Suppl: 1-6,8


Thanksgiving Break Holiday Week


Work on projects, Oral Presentations.pptx

See Online Docs and Chapter 2: pp. 89-90



Review and TEST #2, Study Guide, Sample Test,   Sample test KEY




Presentation of term project to the class, professor and TA


Final Project paper due




Possible Project Topics:

Important Note: Your project needs to work with real world input, i.e. the camera or scanner. You need to design it to be robust, i.e. to handle various sizes, orientations, lighting conditions, etc. If it cannot handle these you need to define a calibration routine that is easy and fast. As part of the demo we will test the robustness via having the program classify "unknown" input.

Week What is due

Suggested Project Process:

·  NOTE: If you do not have any specific images that you want to use, take a look at the image databases on the Internet, such as: DIP Image Databases

ECE 438  Image Analysis and Computer Vision Laboratory Outline

Ø  Students will work in pairs, with a partner of their choice. Labs can be performed using CVIPlab in either C or Matlab

Ø  Labs are due at the beginning of the first class period weeks 5 and 10; Late lab work is worth 50% up until 2 days late, after that it is worth 10%

Ø  Useful document for those familiar with C++, but not C programming: C for C++ Programmers.htm


TOPICS - reading: Chapter 2,  CVIPtools


Chapter 2: Introduction to CVIPlab. Lab1_C or Lab1_Matlab

Chapter 3, p. 145: Image Geometry, parts 1-3

Chapter 3, p. 146: Binary Object Features parts 1&2


Chapter 4, p. 208: Edge Detection - Roberts and Sobel

Chapter 5, p. 270: Morphological Filters,  binary images only


Term project, see section 2.7, p. 89 for ideas

·         Create project proposal

·         Run experiments and analyze results

·         Write report and develop presentation/demo


Present project to the class


ECE 438 Image Analysis & Computer Vision - Semester Project

Semester Project: The project will consist of designing experiments, implementing algorithms, and analyzing the results for a computer vision problem. You will work with a partner. You will get the images for your project by using the cameras in the CVIP lab or your own camera – part of the project is image acquisition. The project will be selected by the students, subject to approval by the professor. The project proposal, due week 11, will include: 1) classes to be identified, 2) number and type of images to be used, 3) potential algorithm(s) for object extraction, 4) classification method(s) to be used, 5) method of evaluation of results. For the image sets, a minimum of four classes and ten images of each class is recommended. In this case, five of each class can be used for training and five for testing.

A paper will be written describing the project and discussing what was learned during the project. The final paper should be about 10 to 15 pages, typed and double-spaced; include images ! In the paper include an appendix containing related data files and/or program listing(s). The students will give a short presentation of their project in the lab to the class, the professor, and the lab instructor. These presentations will take place during the scheduled final exam period, and will be 5 minutes in length. Do NOT go over 5 minutes and do not have more than 10 PowerPoint slides! Also, an evaluation for each group member will be handed in or emailed with the report.

Ø  You do NOT need to hand in a paper copy of the report, email me a soft copy of the Word file. Before you send me the file give it a meaningful name that includes your last name(s) and the project title.

Grading: The project is worth 25% of your term grade, broken down as follows:

  • Overall Project.. 15%
  • Paper................. 5%
  • Presentation........ 5%

NOTES: 1) Start on your project as early in the term as possible, 2) late projects are worth 0.

Project Paper Format Outline

General: reports should be double spaced, pages numbered starting with abstract. Number of pages?- do what is necessary, but keep it concise, extra stuff can go in an appendix.

·         Title page (project title, names, course number, date, etc.)

·         Table of contents with page numbers for: different sections, figures, appendices, etc.

·         Abstract - 1 page or less. Concise description of what is contained in the paper.

·         Introduction/Project overview

·         Body of paper. Broken down into sections as required for you project. For example: Background/theory, experimental methods, discussion and analysis of results, program descriptions, etc. Present results using graphs, images, etc.,

·         Summary and conclusions. Summarize any results and draw conclusions as based on these results.

·         Suggestions for future work. Include any ideas you have based on your work and conclusions about follow-up experiments and/or research.

·         References. Be sure your references are complete. Avoid web sites as references – these come and go – find the source, which is usually a published paper.

·         Appendices - related background information, program listings, etc.


ECE 438 Image Analysis & Computer Vision PowerPoint Lecture Slides

Class Attendance Policy: Based on University Class Attendance Policy 1I9: It is the responsibility of students to ascertain the policies of instructors with regard to absence from class, and to make arrangements satisfactory to instructors with regard to missed course work. Failure to attend the first session of a course may result in the student’s place in class being assigned to another student.


Class Policies:  If you have a documented disability that requires academic accommodations, please go to Disability Support Services for coordination of your academic accommodations. DSS is located in the Student Success Center, Room 1270; you may contact them to make an appointment by calling (618) 650-3726 or sending an email to  Please visit the DSS website located online at:  for more information.


Students are expected to be familiar with and follow the Student Academic Code. It is included in the SIUE Policies and Procedures under Section 3C2.2.


COVID-19 Policies Related to Classroom Instruction

Health and Safety

General Health Measures


At all times, students should engage in recommended health and safety measures, which include:

·         Conducting a daily health assessment.    If you have COVID-19 symptoms, but not yet tested positive, have had COVID-19 close contact exposure, or are COVID-19 diagnosed as presumptive or confirmed positive, stay home and contact your health provider or SIUE Health Service at or 618-650-2842. 

·         Frequent washing or disinfecting of hands.

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Students are reminded that the expectations and academic standards outlined in the Student Academic Code (3C2) apply to all courses, field experiences and educational experiences at the University, regardless of modality or location.  The full text of the policy can be found here:

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Brief Bibliography


·         1. Digital Image Processing - R.C.Gonzalez & P.Wintz

·         2. Robot Vision - B.K.P.Horn

·         3. Computer Vision - D.H.Ballard & C.M.Brown

·         4. Syntactic Pattern Recognition : An introduction -R.C.Gonzalez and M.G.Thomason

·         5. Pattern Recognition - A Statistical Approach - P.A. Devijver and J. Kittler

·         6. Digital Image Processing - W. K. Pratt

·         7. Fundamentals of Digital Image Processing - A.K. Jain

·         8. Digital Picture Processing - A. Rosenfeld and A.C. Kak

·         9. Pattern Classification and Scene Analysis - R.O. Duda and P.E. Hart

·         10. Object Recognition by Computer - W.E.L. Grimson

·         11. Digital Pictures - A.N. Netravali and B.G. Haskell

·         12. Vision in Man and Machine - M.D. Levine

·         13. Pattern Recognition Statistical, Structural and Neural Approaches, R.J Schalkoff, John Wiley & Sons NY

·         14. Digital Image Processing and Computer Vision, R.J. Schalkoff, Wiley

·         15. Artificial Intelligence: An Engineering Approach, R.J. Schalkoff, McGraw-Hill

·         16. Algorithms for Graphics and Image Processing, Theo Pavlidis, Computer Science Press, call no.: T385.P381982

·         17. Handbook of Pattern Recognition and Image Processing, K.S. Fu and T.Y. Young, Academic Press

·         18. The Image Processing Handbook, John C. Russ, CRC Press SIUE Library call #: TA1632.R881992 (reference)


·         1. IEEE Transactions on Pattern Analysis and Machine Intelligence

·         2. IEEE Transactions on Computers

·         3. Pattern Recognition

·         4. Computer Vision, Graphics and Image Processing

·         5. IEEE Transactions on Medical Imaging

·         6. Computerized Medical Imaging and Graphics

·         7. IEEE Transactions on Image Processing

·         8. IEEE Engineering in Medicine and Biology

·         9. IEEE Transactions on Signal Processing

·         10. IEEE Transactions on Neural Networks

·         11. IEEE Transactions on Geoscience and Remote Sensing

·         12. Photogrammetric Engineering and Remote Sensing

·         13. International Journal of Remote Sensing

·         14. Journal of Visual Communication and Image Representation

Numerous Conference Proceedings from the following professional groups:

·         IEEE - Institute of Electrical and Electronic Engineers

·         SPIE - Society of Photographic and Instrumentation Engineers, The International Society for Optical Engineering

·         SMPTE - The Society of Motion Picture and Television Engineers

·         PRS - Pattern Recognition Society