Robust feature detection and local classification for surfaces based on moment analysis

The stable local classification of discrete surfaces with respect to features such as edges and corners or concave and convex regions, respectively, is as quite difficult as well as indispensable for many surface processing applications. Usually, the feature detection is done via a local curvature a...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 10(2004), 5 vom: 14. Sept., Seite 516-24
1. Verfasser: Clarenz, Ulrich (VerfasserIn)
Weitere Verfasser: Rumpf, Martin, Telea, Alexandru
Format: Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Comparative Study Evaluation Study Journal Article
LEADER 01000naa a22002652 4500
001 NLM15446094X
003 DE-627
005 20231223070045.0
007 tu
008 231223s2004 xx ||||| 00| ||eng c
028 5 2 |a pubmed24n0515.xml 
035 |a (DE-627)NLM15446094X 
035 |a (NLM)15794134 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Clarenz, Ulrich  |e verfasserin  |4 aut 
245 1 0 |a Robust feature detection and local classification for surfaces based on moment analysis 
264 1 |c 2004 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 21.04.2005 
500 |a Date Revised 10.12.2019 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a The stable local classification of discrete surfaces with respect to features such as edges and corners or concave and convex regions, respectively, is as quite difficult as well as indispensable for many surface processing applications. Usually, the feature detection is done via a local curvature analysis. If concerned with large triangular and irregular grids, e.g., generated via a marching cube algorithm, the detectors are tedious to treat and a robust classification is hard to achieve. Here, a local classification method on surfaces is presented which avoids the evaluation of discretized curvature quantities. Moreover, it provides an indicator for smoothness of a given discrete surface and comes together with a built-in multiscale. The proposed classification tool is based on local zero and first moments on the discrete surface. The corresponding integral quantities are stable to compute and they give less noisy results compared to discrete curvature quantities. The stencil width for the integration of the moments turns out to be the scale parameter. Prospective surface processing applications are the segmentation on surfaces, surface comparison, and matching and surface modeling. Here, a method for feature preserving fairing of surfaces is discussed to underline the applicability of the presented approach 
650 4 |a Comparative Study 
650 4 |a Evaluation Study 
650 4 |a Journal Article 
700 1 |a Rumpf, Martin  |e verfasserin  |4 aut 
700 1 |a Telea, Alexandru  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on visualization and computer graphics  |d 1996  |g 10(2004), 5 vom: 14. Sept., Seite 516-24  |w (DE-627)NLM098269445  |x 1941-0506  |7 nnns 
773 1 8 |g volume:10  |g year:2004  |g number:5  |g day:14  |g month:09  |g pages:516-24 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 10  |j 2004  |e 5  |b 14  |c 09  |h 516-24