TY - JOUR
T1 - On vector quantization for fast facet edge detection
AU - Jaisimha, M. Y.
AU - Goldschneider, J. R.
AU - Mohr, A. E.
AU - Riskin, E. A.
AU - Haralick, R. M.
PY - 1994
Y1 - 1994
N2 - Presents an approach for performing edge detection which builds on prior work in fast facet edge detection using tree-structured vector quantization (TSVQ). The authors first extend the approach by using larger image vectors to reduce computational complexity by performing edge detection on multiple pixels at once. They then reduce the computational complexity of the edge detector without sacrificing performance by pruning the TSVQ with an edge detection-based criterion. They present results of edge detector performance on a sequence of images obtained from a mobile robot.
AB - Presents an approach for performing edge detection which builds on prior work in fast facet edge detection using tree-structured vector quantization (TSVQ). The authors first extend the approach by using larger image vectors to reduce computational complexity by performing edge detection on multiple pixels at once. They then reduce the computational complexity of the edge detector without sacrificing performance by pruning the TSVQ with an edge detection-based criterion. They present results of edge detector performance on a sequence of images obtained from a mobile robot.
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M3 - Article
AN - SCOPUS:26444525610
SN - 1520-6149
VL - 5
SP - V37-V40
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
M1 - 389517
ER -