ECE 438 Image Analysis &
Computer Vision
Course Syllabus
Professor: Dr. Scott
E Umbaugh Office:
Phone: 650-2524, 2948 e-mail: sumbaug@siue.edu
Textbook: Digital Image Processing and Analysis: Application with MATLAB and CVIPtools, 3rd Edition, SE Umbaugh, Taylor&Francis/CRC Press, 2018
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.
OUTLINE
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%
ECE 438 LECTURE SCHEDULE
Ø Labs are due at the beginning of the
first class period the week after assigned; see late policy below
WEEK |
TOPICS |
|
HOMEWORK & LAB |
1 |
Overview, computer imaging systems, lenses |
Chapter 1: pp. 3-11, Chapter 2: pp.13-23 |
Chap 1: 1-6 Chap 2: 1-4, 6-12, suppl: 1,4 |
2 |
Image formation and sensing, CVIPlab |
Chapter 2: pp. 24-76, Chapter 11: pp. 631-669 |
Chap 2:13-15,21,25,27; suppl: 2,7 Lab: Intro CVIPlab |
3 |
Image analysis, preprocessing |
Chapter 3: pp. 69-93 |
Chap 3: 1,2,3,6,9,10,12,13,15,21 Lab: Image Geometry, parts 1-3 |
4 |
Binary image analysis |
Chapter 3: pp. 93-113 |
Chap 3: 23-28, suppl: 1,2 Lab: Binary Object Features, parts 1,2,3,4 |
5 |
Edge detection |
Chapter 4: pp. 121-144 |
Chap4:1-9,11,14,15 Lab: Edge Detection-Roberts&Sobel |
6 |
Edge detection performance, Hough transform, corner detection |
Chapter 4: pp. 144-165 |
Chap 4: 17-21, suppl:1,2,3,11 Not collected due to test |
7 |
Review and TEST #1, Study Guide, Sample test, Sample test KEY |
|
|
8 |
Segmentation |
Chapter 4: pp. 165-182 |
Chap 4: 22-26 Suppl:4,6 Lab: Histogram Thresholding Segmentation |
9 |
Morphological filtering |
Chapter 4: pp. 182-213 |
Chap 4: 27-30 Suppl:9,10 Lab: Morphological Filters |
10 |
Fourier transform Project proposal due Must be approved by Professor |
Chapter 5: pp. 225-248 Chapter 11: pp. 669-672 |
Chap 5: 1-10, suppl: 1,2 Project |
11 |
Feature extraction, shape, histogram, color, spectral, texture, using CVIPtools |
Chapter 6: pp. 295-317 |
Chap 6: 1-6, 8, 11-17 Project |
12 |
Feature analysis, feature vectors, distance /similarity measures, data preprocessing |
Chapter 6: pp. 317-326 |
Chap 6:18-22 Project |
13 |
Pattern classification |
Chapter 6: pp. 326-345 |
Chap 6: 23-27,30 Project |
14 |
Projects, Oral Presentations.pptx |
Chapter 11: pp. 669-672 |
Project |
15 |
Review and TEST #2, Study Guide, Sample Test, Sample test KEY |
|
|
16 |
Presentation of term project to the class, professor and TA Final Project paper due |
|
|
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 10, 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
In addition to handing 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:
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 typed, 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. DO NOT put in plastic folder, simply staple in upper left hand corner.
Week |
TOPICS - reading: Section 2.3, Chapter 11, Appendices, CVIPtools |
1&2 |
Chapter2: Introduction to CVIPlab. |
3 |
Chapter 3: Image Geometry, parts 1-3, part 4 (rotation) for extra credit |
4 |
Chapter 3: Binary Object Features, parts 1,2,3,4, part 5 for extra credit |
5 |
Chapter 4: Edge Detection – Roberts and Sobel |
6 |
(Study) |
7 |
(Test #1) |
8 |
Chapter 4: Histogram Thresholding Segmentation |
9 |
Chapter 4: Morphological Filters, binary images only, gray scale/color for extra credit |
10 |
Project proposal due. Chap 11 |
11-15 |
Work on project: application of pattern classification |
16 |
Present project to the class |
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Brief Bibliography
Books
Journals
Numerous Conference Proceedings from the following professional groups: