|
Abstract: Based
on differential-geometry features of edge curves, a new data
segmentation method is proposed to segment the unorganized noise
point-cloud. An algorithm revised from the TAUBIN’s paper is put forward
first to estimate the principle curvatures and principle directions of
the unorganized noise points. By analyze the variability of curvature in
principle direction for each point, the G1
or G2
continuous edge-points can be detected. The acquired edge-points form
into edge stripes, which segment the point-cloud into a few
sub-regions. Finally a region-growing way is adopted to identify every
sub-area. Results indicate that the presented method can overcome noise
influence and recognize the G1
and G2
edges of unorganized noise point-cloud effectively, and the method can
directly acquire good G2
edges of the complicated object.
Key words: Unorganized noise point-cloud
Data segmentation Curvature estimation
CLC No: TP391
Received 20060305, received in revised form 20061022
|