Proceedings of SPIE - the International Society for Optical Engineering
In an effort to make automatically detect image features for pattern recognition, we described a 3-dimensional (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.
Cofer, R. H., Kozaitis, S. P., & Cha, J. (2003). Extended hough methodology for 3-D feature detection. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 5243 158-164