An adaptative filtering method to evalute normal vectors and surface areas of 3d objects. Application to snow images from X-ray tomography

Abstract : Estimating the normal vector field on the boundary of discrete 3D objects is essential for rendering and image measurement problems. Most of the existing algorithms do not provide an accurate determination of the normal vector field for shapes that present edges. We propose here a new and simple computational method in order to obtain accurate results on all types of shapes whatever their local convexity degree is. The presented method is based on the gradient vector field analysis of the object distance map. This vector field is adaptively filtered around each surface voxel using angle and symmetry criteria, so that as many relevant contributions as possible are accounted for. This optimizes the smoothing of digitization effects while preserving relevant details of the processed numerical object. Thanks to the precise normal field obtained, a projection method can be proposed to derive immediately the surface area from a raw discrete object. An empirical justification of the validity of such an algorithm in the continuous limit is also provided. Some results on simulated data and snow images from X-ray tomography are presented, compared to the Marching Cubes and Convex Hull results and discussed.
Document type :
Journal articles
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-00185086
Contributor : David Coeurjolly <>
Submitted on : Monday, November 5, 2007 - 12:38:28 PM
Last modification on : Wednesday, April 3, 2019 - 1:06:04 AM
Long-term archiving on : Monday, April 12, 2010 - 1:18:02 AM

File

Flin-2005_liris1236.pdf
Publisher files allowed on an open archive

Identifiers

  • HAL Id : hal-00185086, version 1

Citation

Frédéric Flin, Jean-Bruno Brzoska, David Coeurjolly, Romeu Pieritz, Bernard Lesaffre, et al.. An adaptative filtering method to evalute normal vectors and surface areas of 3d objects. Application to snow images from X-ray tomography. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2005, 14 (5), pp.585-596. ⟨hal-00185086⟩

Share

Metrics

Record views

1186

Files downloads

489