An Approach for Efficient Detection of Cephalometric Landmarks | Zendy

Thuong Le-Tien | Zendy; Chi-Hieu Pham | Zendy

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An Approach for Efficient Detection of Cephalometric Landmarks

Author(s) -

Thuong Le-Tien,

Chi-Hieu Pham

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.08.044

Subject(s) - computer science , thresholding , artificial intelligence , edge detection , computer vision , enhanced data rates for gsm evolution , process (computing) , histogram , support vector machine , canny edge detector , mandible (arthropod mouthpart) , pattern recognition (psychology) , image processing , image (mathematics) , botany , biology , genus , operating system

In this paper, a method is developed for the automated identification of cephalometric landmarks in orthodontics. The process of soft tissue edge detection is divided into two steps: detecting the sub-images that contained the required landmarks using combination of the Histograms of Oriented Gradients (HOG) descriptor with the Support Vector Machine (SVM), then utilizing Thresholding and Mathematical Morphological (TMM) algorithm to trace soft tissue profile. In addition, the mandible's edge is detected by the Active contours without edges (Chan-Vese method). Finally, the landmarks of soft tissue profile and the mandible's edge are pinned based on analyzing the contour plot of these lines. The simulation results have high accuracy

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