Casualty Identification with Dental Radiographs and Photographs

Abstract

A biometric system is used to identify and authenticate a person based on the information, which are unique biological traits to work effectively. Physiological biometrics such as fingerprint, face, iris, etc., provide reliable information for human identification. However, most of these cannot be used in the case of identifying a person after a disaster. In this paper a dental biometric technique is presented based on dental radiographs and photographs. It is aimed to obtain casualty identification with photographs, in circumstances where radiographs are unavailable. Here, it is proposed to improve the shape extraction performance by using shape descriptors and skeleton. The obtained data from the test image are compared with the set of database images and the best match is obtained for authentication. An improved nodal-based matching is proposed with both dental radiographs and photographs to improve the matching rate. The final matching is carried out with both the shape information and nodal graphs obtained. The hit rate obtained is comparable with the existing algorithm with a rank −1 accuracy of 78%.

KEYWORDS:

• Dental photographs
• Dental radiographs
• Forensic department
• Nodal graph
• Person identification
• Signatures

ACKNOWLEDGEMENTS

The authors would like to thank the Principal and Department of ECE, Mepco Schlenk Engineering College, Sivakasi for providing all the facilities to carry out this work successfully.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

B. Vijayakumari

B Vijayakumari completed the BE at the Institute of Road and Transport Technology, Erode during 1997 and received the ME (communication systems) from Thiagarajar College of Engineering, Madurai, in 2006. She completed PhD in medical image processing at Thiagarajar College of Engineering,Madurai, Anna University in 2014 and is currently working as associate professor in the Department of ECE at Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu. Her areas of research include medical image processing and image analysis. Her research publications include a few peer-reviewed and Science Citation-Indexed journals with publishers such as Springer, Elsevier, IET, Inderscience, IETE, SPIE, etc. and a few national and international conferences. She is a Life Member of Indian Society for Technical Education (ISTE) and the Institution of Electronics and Telecommunication Engineers. Corresponding author. Email: [email protected]

M. Vasanthal

M Vasanthal completed the BE graduation in electronics and communication engineering from Mepco Schlenk Engineering College, Sivakasi in 2020. She is currently working as software engineer at HCL Technologies. Her research area covers medical image processing. Email: [email protected]

S. Dhivya Dharshini

S Dhivya Dharshini completed the BE in electronics and communication engineering from Mepco Schlenk Engineering College, Sivakasi in 2020. She is currently working as a program analyst at Cognizant Technology Solutions. Her research area covers medical image processing. Email: [email protected]