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Proceedings Paper

Extended Hough methodology for 3D feature detection
Author(s): Rufus H. Cofer; Samuel Peter Kozaitis; Jihun Cha
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Paper Abstract

In an effort to make automatically detect image features for pattern recognition, we described a 3-dimesional (3-D) Hough transform. We describe two interlocking theoretical extensions to greatly enhance the Hough transform's ability to handle finite lineal features and allow directed search for various features while balancing memory and computational complexity. We computed the 2-D Hough transform of 1-D slices of an image which results in a 2-D to 3-D transform. Features such as line segments will cluster in a particular location so that both line orientation and spatial extent can be determined. This approach allows the Hough transform to be more widely applied in pattern recognition including 3-D features.

Paper Details

Date Published: 26 November 2003
PDF: 7 pages
Proc. SPIE 5243, Three-Dimensional TV, Video, and Display II, (26 November 2003); doi: 10.1117/12.511256
Show Author Affiliations
Rufus H. Cofer, Florida Institute of Technology (United States)
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Jihun Cha, Florida Institute of Technology (United States)

Published in SPIE Proceedings Vol. 5243:
Three-Dimensional TV, Video, and Display II
Bahram Javidi; Fumio Okano, Editor(s)

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