Features Extraction and Matching of Teeth Image Based on the SIFT Algorithm

DOI

10.2991/iccasm.2012.123How to use a DOI?

Keywords

SIFT, feature extraction, teeth image

Abstract

Using of SIFT algorithm in the image of teeth model, can detect the features of the teeth image effectively. In this approach, first, search over all scales and image locations by using a difference-of-Gaussian function to identify potential interest points that are invariant to scale and orientation. Second, select keypoints based on measures of their stability and a detailed model is fit to determine location and scale at each candidate location. Third, assign one or more orientations to each keypoint location based on local image gradient directions. Last, measure the local image gradients at the selected scale in the region around each keypoint. And then use the KNN algorithm to match the features. Through lots of experiments and comparing with other feature extraction methods, this method can detect the features of the teeth model effectively, and offer some available parameters for 3D reconstruction of the teeth model.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xinzui Wang
AU  - Huanli Li
AU  - Ningning Dong
PY  - 2012/08
DA  - 2012/08
TI  - Features Extraction and Matching of Teeth Image Based on the SIFT Algorithm
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 483
EP  - 486
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.123
DO  - 10.2991/iccasm.2012.123
ID  - Wang2012/08
ER  -