Three-dimensional positions of the visible surfaces in stereo images can be determined by simple trigonometric transformation once the stereo matching problem is solved. Most existing stereo matching methods involve matching low-level image features such as edges. This research describes an improved stereo matching procedure based on matching high-level image features. New techniques for extracting high-level image features will be explored with the aim of extracting a rich symbolic representation of the gray intensity changes in an image. Methods will be developed for determining correspondences between the extracted image features in the stereo images. The goal is to develop algorithms for generating full disparity maps for stereo images.

Project Start
Project End
Budget Start
1985-07-01
Budget End
1988-06-30
Support Year
Fiscal Year
1985
Total Cost
$59,901
Indirect Cost
Name
University of Minnesota Saint Paul
Department
Type
DUNS #
City
Minneapolis
State
MN
Country
United States
Zip Code
55455