Abstract
Teeth are difficult to be destroyed due to their corrosion resistance, high melting point and hardness. Dental biometrics can therefore provide assistance in human forensic identification, especially to the unknown corpses. One of the key issue in dental based human identification is the segmentation of Dental X-ray images. In this paper, a novel segmentation algorithm has been proposed for this purpose. The proposed algorithm is based on full threshold segmentation. We first obtain the outline image set Iwholen and crown image set Icrownm of the complete target tooth. Morphological open operation is then applied to the difference images of Iwholen and Icrownm. Subsequently, the most complete target tooth image and its corresponding crown image are selected. Getting independent target tooth image Icontour and its crown image Icrown from these two images. Median filtering is applied to the synthetic image of Icontour and Icrown, and the resulted image will be used as the Mask for GrabCut to obtain the target tooth image. Experimental results show our proposed algorithm can effectively overcome the problems of uneven grayscale distribution and adhesion of adjacent crowns in dental X-ray images. It can also achieve a high segmentation accuracy and outperform related methods to be compared.
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