Fall 2003 (Section 09209)
2:30pm - 4:00pm, Monday & Wednesday
Room LC-01
URL: http://www.vcl.uh.edu/~6373f03/index.html

Instructor: Ioannis Kakadiaris (ioannisk@uh.edu)
Office Hours (PGH 219): 4:00pm - 4:30pm Mon & Wed

Goals:

This course offers an introduction to computer vision and machine perception.  Computer vision describes the automatic deduction of the properties and the structure of a three-dimensional world from one or more monochromatic (or colored) two-dimensional images. The robotic control of an unmanned lunar rover, the automatic classification of blood cells in medical images and the detection of faults in seismic data are examples of computer vision applications.  This course is intended to provide material of interest to students in science and engineering at the graduate level, with examples drawn from all the major industries of the Houston area (e.g. NASA, Medical Center, Oil industry).

Topics to be covered:

•  What is Computer Vision?
•  Image Formation & Representation
•  Image Pre-Processing
•  Edge/Line Detection
•  Image Segmentation
•  Shape Representation
•  Image Data Compression
•  Motion Analysis

Prerequisites

Programming in C or C++, Linear Algebra and  Calculus.

Evaluation

The course grade will be computed as follows:

Assignments	50%
Midterm	15%
Final	25%
Class Participation	10%

Textbooks

• Milan Sonka, Vaclav Hlavac, Roger Boyle: Image Processing, Analysis, and Machine Vision, Brooks/Cole Publishing Company, 1998, Second Edition
• David Forsyth, Jean Ponce: Computer Vision - A Modern Approach, Prentice Hall, 2003