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An effective dental shape extraction algorithm using contour information and matching by Mahalanobis distance
Vijayakumari Pushparaj1, Ulaganathan Gurunathan, Banumathi Arumugam
1Thiagarajar College of Engineering, Madurai, Tamilnadu, India. vijayakumari@tce.edu
Journal of Digital Imaging
|June 15, 2012
Summary
This study presents an automated system for human identification using dental radiographs. The method enhances tooth contour extraction and matching for improved accuracy in biometric identification.
Area of Science:
- Biometrics
- Forensic Dentistry
- Computer Vision
Background:
- Dental radiographs are crucial for human identification, especially in mass disaster scenarios like the 2004 tsunami.
- Accurate and efficient identification methods are vital for forensic applications.
Purpose of the Study:
- To develop an automated person identification system using dental radiographs.
- To improve upon existing semi-automatic methods for dental record matching.
Main Methods:
- A four-stage process involving preprocessing, integral intensity projection for segmentation, and shape extraction using fast connected component labeling.
- Utilizing tooth contour information for feature extraction.
- Employing the Mahalanobis distance measure for matching dental records.
Main Results:
- The proposed automated method achieves improved matching accuracy compared to previous semi-automatic contour extraction techniques.
- Fast connected component labeling enhanced the robustness of shape extraction for misaligned images.
Conclusions:
- Automated analysis of dental radiographs offers a promising approach for reliable human identification.
- Tooth contour-based feature extraction and Mahalanobis distance matching provide effective biometric solutions.
