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Proceedings Paper

Feature detection on 3D images of dental imprints
Author(s): Marielle Mokhtari; Denis Laurendeau
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Paper Abstract

A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

Paper Details

Date Published: 9 September 1994
PDF: 12 pages
Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); doi: 10.1117/12.185224
Show Author Affiliations
Marielle Mokhtari, Univ. Laval (Canada)
Denis Laurendeau, Univ. Laval (Canada)


Published in SPIE Proceedings Vol. 2359:
Visualization in Biomedical Computing 1994
Richard A. Robb, Editor(s)

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