THE USE OF DENTAL RADIOGRAPHIC IMAGE ANALYSIS IN IDENTIFICATION OF DECEASED INDIVIDUALS

Article Sidebar

pdf
Published: Jun 1, 2009
DOI: https://doi.org/10.31026/j.eng.2009.02.11

Main Article Content

Hana' S. Basheer
Ahmed A.H. Hindy

Abstract

Dental records recently used in forensic medicine to help in human identification, based mainly on radiograph images. The aim of our study is to automate this process, using image analysis and pattern recognition techniques. Postmortem radiographs, including dental radiographs, with a database of ante mortem radiographs searching, in order to get the closest match with respect to some distinct features. Contours of teeth are used as the feature for matching, since they remain more invariant over time compared to some other features of the body. The work ineludes two stages: radiograph segmentation, with pixel classification, and contour matching Probability model is used to describe the distribution of object pixels in the image. Results of retrievals on a database of over 40 images are encouraging.

Article Details

How to Cite
“THE USE OF DENTAL RADIOGRAPHIC IMAGE ANALYSIS IN IDENTIFICATION OF DECEASED INDIVIDUALS” (2009) Journal of Engineering, 15(2), pp. 3666–3672. doi:10.31026/j.eng.2009.02.11.
Issue
Vol. 15 No. 2 (2009): journal of engineering
Section
Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

 
 

How to Cite

“THE USE OF DENTAL RADIOGRAPHIC IMAGE ANALYSIS IN IDENTIFICATION OF DECEASED INDIVIDUALS” (2009) Journal of Engineering, 15(2), pp. 3666–3672. doi:10.31026/j.eng.2009.02.11.
Crossref
Scopus
Google Scholar
Europe PMC

Publication Dates

References

Deriche R., "Using Canny's Criteria to Derive an Optimal Edge Detector Recursively Implemented", Int. J. Computer Vision, Vol. 1, pp. 167-187. April 1987.

Jain A. K., and Chen H.. J. Pattern Recognition Society, 37(2004) 1519-1532, "Matching of dental X-ray images for human identification Hoffman G.. "Gaussian Filters"., website, retrieved on (March/15/2007) from http://www.fho emden.de/-hoffmann gauss25092001 pdf Kinnebrock W., "Neural networks, fundamentals, applications, and examples", 2"ª revised edition.

R. Oldenbourg Publishing House Munich-Vienna. 1995.

Kinouchil M., Kinouchi N. T., Kuđol Y.. and Ikemura T. "quick learning for bateh-learning self organizing map".. Genome Informaties 13. pp. 266-267, 2002.

Langlais R. P., and Kasle M. J., "Exercises in Oral Radiographic Interpretation", W. B. Saunders Company, p.129, 1985 -Umbaugh S. E., Ph. D. "Computer vision and image processing: A practical approach using CVIP tools". Prentice Hall PTR Prentice-Hall. Inc 1998

-Venkatesh Y. V., Raja S. K., and Ramya N., "Multiple contour extraction from grav level images usmg an artificial neural network"". IETE transactions on image processitg. Voli, 15. NoA. Anrl 2006