Extended Hough methodology for 3D feature detection

Rufus H. Cofer; Samuel Peter Kozaitis; Jihun Cha

doi:10.1117/12.511256

26 November 2003 Extended Hough methodology for 3D feature detection

Rufus H. Cofer, Samuel Peter Kozaitis, Jihun Cha

Proceedings Volume 5243, Three-Dimensional TV, Video, and Display II; (2003) https://doi.org/10.1117/12.511256
Event: ITCom 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Rufus H. Cofer, Samuel Peter Kozaitis, and Jihun Cha "Extended Hough methodology for 3D feature detection", Proc. SPIE 5243, Three-Dimensional TV, Video, and Display II, (26 November 2003); https://doi.org/10.1117/12.511256

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