9.913 Pattern Recognition for Machine Vision

Fall 2004

Series of images illustrating color and position clustering.

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.)

Course Highlights

This course features animations and downloadable lecture notes.

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

RealOne™ Player software is required to run the .rm files found on this course site.

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Staff

Instructors:
Dr. Bernd Heisele
Dr. Yuri Ivanov

Course Meeting Times

Lectures:
One session / week
2 hours / session

Level

Graduate

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