A New Approach to Teeth Segmentation

Abstract

Teeth segmentation is one of the important components in building an Automated Dental Identification System (ADIS). The extraction of the teeth from their corresponding dental radiographs is called teeth segmentation. Dental radiographs may suffer from poor teeth image quality, low contrast and uneven exposure that complicate the task of teeth segmentation. To achieve a good performance in segmentation, the teeth images are preprocessed by a two-step thresholding technique, which starts with an iterative thresholding followed by an adaptive thresholding to binarize the teeth images. Then, we propose to adapt the seam carving technique on the binary images, using both horizontal and vertical seams, to separate each individual tooth. The proposed method is evaluated experimentally and compared to other algorithms. The results show that our new approach achieves the lowest failure rate among all existing methods, and the highest optimality among all of the fully automated approaches reported in the literature.