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Proceedings Paper

Edge detection and labeling by fusion of intensity and range images
Author(s): Sateesha G. Nadabar; Anil K. Jain
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Paper Abstract

We have developed an energy minimization approach for detection and labeling of edges by fusing information from registered intensity and range images. The chosen set of labels for the edges (jump, crease, intensity, no edge) is a classification based on the physical properties of the surfaces in the scene. Bayesian formulation is used to combine the different information sources and the a priori knowledge about the labels is modeled by a Markov random field. Results of applying the labeling algorithm on several real image pairs indicate that it is possible to detect as well as label the jump, crease, and intensity edges accurately using this approach.

Paper Details

Date Published: 1 March 1992
PDF: 12 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58565
Show Author Affiliations
Sateesha G. Nadabar, Michigan State Univ. (United States)
Anil K. Jain, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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