Authors:
Selma Guzel
1
;
Ayse Betul Oktay
2
and
Kadir Tufan
3
Affiliations:
1
Gebze Institute of Technology, Turkey
;
2
Istanbul Medeniyet University, Turkey
;
3
Fatih University, Turkey
Keyword(s):
Tooth detection, Tooth labeling, Haar, SVM, Atlas-based Model.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Bioinformatics and Systems Biology
;
Computer Vision, Visualization and Computer Graphics
;
Image Understanding
;
Medical Imaging
;
Pattern Recognition
;
Software Engineering
Abstract:
After catastrophes and mass disasters, accurate and efficient identification of decedents requires an automatic
system which depends upon strong biometrics. In this paper, we present an automatic tooth detection and
labeling system based on panoramic dental radiographs. Although our ultimate objective is to identify decedents
by comparing the postmortem and antemortem dental radiographs, this paper only involves the tooth
detection and the tooth labeling stages. In the system, the tooth regions are first determined and the detection
module runs for each region individually. By employing the sliding window technique, the Haar features are
extracted from each window and the SVM classifies the windows as tooth or not. The labeling module labels
the candidate tooth positions determined by the SVM with an atlas-based model and the final tooth positions
are inferred. The novelty of our system is combining the atlas-based model with the SVM under the same
framework. We tested our system on
35 panoramic images and the results are promising.
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