Dental radiographs and photographs in human forensic identification

Dental radiographs and photographs in human forensic identification

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Dentistry can contribute for the identification of human remains after any disasters or crimes in assistance to other medical specialties. The algorithm can be developed by comparing post mortem and ante mortem dental radiographs. This work aims to introduce photographic images in addition to radiographs. In this research a contour and skeleton-based shape extraction as well as matching algorithm for dental images is proposed. An active contour model with selective binary and Gaussian filtering regularised level set method is used for contour extraction. Shape matching is done by both contour and skeleton-based approaches. The experimental results are obtained from a database of dental images include both radiographs and photographs. This algorithm provides better matching decision about the person than the existing algorithms since it includes skeleton measures also. The performance measures obtained and the hit-rate indicates that the better matching is observed with radiographic than the photographic images.


    1. 1)
      • 1. Savio, C., Merlati, G., Danesino, P., Fassina, G., Menghini, P.: ‘Radiographic evaluation of teeth subjected to high temperatures: experimental study to aid identification processes’, Forensic Sci. Int., 2006, 158, (2), pp. 108116 (doi: 10.1016/j.forsciint.2005.05.003).
    2. 2)
      • 2. Auerkari, E.: ‘Recent trends in dental forensics’, Indonesian J. Legal Forensic Sci., 2008, 1, (1), pp. 512.
    3. 3)
      • 3. Petjua, M., Suteerayongprasertb, A., Thongpudc, R., Hassirid, K.: ‘Importance of dental records for victim identification following the Indian Ocean tsunami disaster in Thailand’, J. R. Inst. Public Health, 2007, 121, pp. 251257.
    4. 4)
      • 4. Anil Jain, K., Chen, H.: ‘Matching of dental X-ray images for human identification’, Pattern Recognit., 2004, 37, pp. 15191532 (doi: 10.1016/j.patcog.2003.12.016).
    5. 5)
      • 5. Banumathi, A., Vijayakumari, B., Raju, S.: ‘Performance analysis of various techniques applied in Human identification using Dental X-Rays’, J. Med. Syst., 2007, 31, (3), pp. 210218 (doi: 10.1007/s10916-007-9057-0).
    6. 6)
      • 6. Pushparaj, V., Gurunathan, U., Arumugam, B.: ‘An effective dental shape extraction algorithm using contour information and matching by mahalanobis distance’, J. Digit. Imaging, 2013, 26, (2), pp. 259263 (doi: 10.1007/s10278-012-9492-4).
    7. 7)
      • 7. Pushparaj, V., Gurunathan, U., Arumugam, B.: ‘Human forensic identification using similarity and distance metrics’. Proc. Eighth Annual IEEE India Conf. INDICON, Cochin, India, December 2012.
    8. 8)
      • 8. Said, E.H., Nassar, D.E., Gamal Fahmy, M., Hany Ammar, H.: ‘Teeth segmentation in digitized dental X-ray films using mathematical morphology’, IEEE Trans. Inf. Forensics Sec., 2006, 1, (2), pp. 178189 (doi: 10.1109/TIFS.2006.873606).
    9. 9)
      • 9. Nomir, O., Abdel-Mottaleb, M.: ‘Human identification from Dental X-Ray images based on the shape and appearance of the teeth’, IEEE Trans. Inf. Forensics Sec., 2007, 2, (2), pp. 188197 (doi: 10.1109/TIFS.2007.897245).
    10. 10)
      • 10. Nomir, O., Abdel-Mottaleb, M.: ‘Fusion of matching algorithms for human identification using dental X-ray radiographs’, IEEE Trans. Inf. Forensics Sec., 2008, 3, (2), pp. 223233 (doi: 10.1109/TIFS.2008.919343).
    11. 11)
      • 11. Nomir, O., Abdel-Mottaleb, M.: ‘Hierarchical contour matching for dental X-ray radiographs’, Pattern Recognit., 2008, 41, (1), pp. 130138 (doi: 10.1016/j.patcog.2007.05.015).
    12. 12)
      • 12. Hosntalab, M., Zoroofi, R.A., Tehrani-Fard, A.A., Shirani, G.: ‘Automated dental recognition in MSCT images for human identification’. Fifth Int. Conf. Intelligent Information Hiding and Multimedia Signal Processing-IEEE, 2009, pp. 13181321.
    13. 13)
      • 13. Lin, P.L., Lai, Y.H., Huang, P.W.: ‘An effective classification and numbering system for dental bitewing radiographs using teeth region and contour information’, Pattern Recognit., 2009, 45, (3), pp. 113.
    14. 14)
      • 14. Aeini, F., Mahmoudi, F.: ‘Classification and numbering of posterior teeth in bitewing dental images’. Third Int. Conf. Advanced Computer Theory and Engineering (ICACTE), 2010, pp. 6672.
    15. 15)
      • 15. Hosntalab, M., Zoroofi, R.A., Tehrani-Fard, A.A., Shirani, G.: ‘Classification and numbering of teeth in multi-slice CT images using wavelet-Fourier descriptor’, Int. J. CARS, 2010, 5, pp. 237249 (doi: 10.1007/s11548-009-0389-8).
    16. 16)
      • 16. Tinoco, R.L.R., Martins, E.C., Daruge, Jr.E., Prado, F.B., Caria, b.P.H.F.: ‘Dental anomalies and their value in human identification: A case report’, J. Forensic Odontostomatol., 2010, 28, (1), pp. 3943.
    17. 17)
      • 17. Al-Amad, S.H.: ‘Forensic odontology’, Smile Dental J., 2009, 4, (1), pp. 2224.
    18. 18)
      • 18. Silva, R.F., Pereira, S.D., Prado, F.B., Daruge, Jr.E.: ‘Forensic odontology identification using smile photograph analysis – case reports’, J. Forensic Odontontostomatol., 2008, 27, (1), pp. 1217.
    19. 19)
      • 19. Kass, M., Witkin, A., Terzopoulos, D.: ‘Snakes: active contour models’, Int. J. Comput. Vis., 1988, 1, pp. 321331 (doi: 10.1007/BF00133570).
    20. 20)
      • 20. Tsai, A., Yezzi, A., Allan Willsky, S.: ‘Curve evolution implementation of the mumford–shah functional for image segmentation, denoising, interpolation, and magnification’, IEEE Trans. Image Process., 2001, 10, (8), pp. 11691186 (doi: 10.1109/83.935033).
    21. 21)
      • 21. Tony Chan, F., Luminita Vese, A.: ‘Active contours without edges’, IEEE Trans. Image Process., 2001, 10, (2), pp. 266277 (doi: 10.1109/83.902291).
    22. 22)
      • 22. Lie, J., Lysaker, M., Tai, X.C.: ‘A binary level set model and some application to Munford–Shah image segmentation’, IEEE Trans. Image Process., 2006, 15, pp. 11711181 (doi: 10.1109/TIP.2005.863956).
    23. 23)
      • 23. Xu, C.Y., Yezzi, Jr.A., Prince, J.L.: ‘On the relationship between parametric and geometric active contours’. Processing of 34th Asilomar Conf. Signals Systems and Computers, 2000, pp. 483489.
    24. 24)
      • 24. Zhang, K., Zhang, L., Song, H., Zhou, W.: ‘Active contours with selective local or global segmentation: A new formulation and level set method’, Image Vis. Comput., 2010, 28, pp. 668676 (doi: 10.1016/j.imavis.2009.10.009).

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