9.913 Pattern Recognition for Machine Vision
As taught in: Fall 2004
Example of color and position clustering: Each pixel is represented by a its color/position features (R, G, B, wx, wy), where w is a constant. Clustering is applied to group pixels with similar color and position. (Image by Dr. Bernd Heisele.)
Level:
Graduate
Instructors:
Dr. Bernd Heisele
Dr. Yuri Ivanov
Course Features
Course Description
The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering.
Technical Requirements
Special software is required to use some of the files in this course: .rm.
