Open AccessGrabCut algorithm for dental X‐ray images based on full threshold segmentation
Author(s) -
Mao Jiafa,
Wang Kaihui,
Hu Yahong,
Sheng Weiguo,
Feng Qixin
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.5730
Subject(s) - artificial intelligence , segmentation , computer vision , biometrics , image segmentation , grayscale , computer science , scale space segmentation , image texture , image (mathematics) , crown (dentistry) , identification (biology) , pattern recognition (psychology) , dentistry , medicine , botany , biology
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 Iwhole n and crown image set Icrown m of the complete target tooth. Morphological open operation is then applied to the difference images of Iwhole n and Icrown m . Subsequently, the most complete target tooth image and its corresponding crown image are selected. Getting independent target tooth image I contour and its crown image I crown from these two images. Median filtering is applied to the synthetic image of I contour and I crown , 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.