Stereo vision system with the grouping process of multiple reaction-diffusion models
Lecture Notes in Computer Science
published_at 2005-06
Title
Stereo vision system with the grouping process of multiple reaction-diffusion models
Creator Keywords
Image segmentation
Mathematical models
Problem solving
The present paper proposes a system that detects a stereo disparity map from random-dot stereograms with the grouping process. A simple operation for random-dot stereograms converts the stereo correspondence problem to the segmentation one. For solving the segmentation problem derived from random-dot stereograms, the stereo vision system proposed here utilizes the grouping process of our previously proposed model. The model for the grouping process consists of multiple reaction-diffusion models, each of which governs segments having a disparity in the stereo vision system. A self-inhibition mechanism due to strong inhibitory diffusion within a particular reaction-diffusion model and a mutual-inhibition mechanism among the models are built in the proposed system. Experimental results for artificially generated random-dot stereograms show the validity of the proposed system.
Languages
eng
Resource Type
conference paper
Publishers
Springer Verlag
Date Issued
2005-06
File Version
Not Applicable (or Unknown)
Access Rights
metadata only access
Relations
[ISSN]0302-9743