DETERMINATION OF THE USABILITY LIMITS OF AURICLE MORPHOLOGY FOR IDENTIFICATION

Yıl 2012, Cilt: 26 Sayı: 2, 56 - 61, 31.08.2012

Mahmut Aşırdizer Ertuğrul Tatlısumak Beyhan Özyurt Mehmet Sunay Yavuz

https://izlik.org/JA68HE49SG

Öz

Objective:
In the present study, it was aimed
to evaluate the usability of morphological appearance of ears for
positive and negative identification and to define the accuracy rates in ear identification using naked-eye detection by experienced
volunteers.
Methods:
This study was performed in three
stages: the gathering of 120 ear
images (60 rights and 60 lefts) of
30 male and 30 female volunteers
(between 18-26 ages), the observation by 20 volunteers experienced on the identification, and the
statistical analysis with SPSS-11
Statistics Program.
Results:
The rates of correct responses
were 86.5 % by proportional calculation and 99.73 % by probability calculation. Whilst the total
rates of wrong responses were
12.5 % by proportional calculation
and 0.25 % by probability calculation in male volunteers, they were
14.5 % by proportional calculation
and 0.29 % by probability calculation in female volunteers (p>0.05)
respectively. The total rates of
wrong responses were more than
twice in left ears than right ears.
Conclusion:
One-to-one matching of ear images with naked eyes can be used
as a part of first elimination carried out by police officers in order
to differentiate the perpetrator(s)
of a crime among suspicious persons.

Anahtar Kelimeler

personal identification , ear images , auricle

Kaynakça

• Curiel López de Arcaute AM, Navarro JG. La huella de oreja como método de identificación [Ear print as an identification method]. Acta Otorrinolaringol Esp 2006;57(7):329-32.
• Bozkir MG, Karakaş P, Yavuz M, Dere F. Morphometry of the external ear in our adult population. Aesthetic Plast Surg 2006; 30(1): 81- 5.
• Brucker MJ, Patel J, Sullivan PK. A morphometric study of the external ear: ageand sex- related differences. Plast Reconstr Surg 2003; 112(2): 647- 52.
• Jain AK, Ross A, Prabhakar S. An introduction to biometric recognition. IEEE Trans Circuits Syst Video Tech 2004; 14(1): 4-20; doi:10.1109/TCSVT.2003.818349
• Heathcote JA. Why do old men have big ears? BMJ 1995; 311(7021): 1668.
• Ito I, Imada M, Ikeda M, Sueno K, Arikuni T, Kida A. A morphological study of age changes in adult human auricular cartilage with special emphasis on elastic fibers. Laryngoscope 2001; 111(5): 881-6.
• Kalcioglu MT, Miman MC, Toplu Y, Yakinci C, Ozturan O. Anthropometric growth study of normal human auricle. Int J Pediatr Otorhinolaryngol 2003; 67(11): 1169-77.
• Van der Lugt C. Ear identification. In: The art and sciences of criminal investigation. Crime& Clues. 1997. http://www.crimeandclues.com/index.php/physical-evidence/ impression-evidence/62-ear-identification. Accessed 27 December 2009.
• Feenstra L, van der Lugt C. Ear witness. J Laryngol Otol 2000; 114(7): 497-500.
• Alberink I, Ruifrok A. Repeatability and reproducibility of earprint acquisition. J Forensic Sci 2008; 53(2): 325-30.
• Alberink IB, Ruifrok AC, Kieckhoefer H. Interoperator test for anatomical annotation of earprints. J Forensic Sci 2006; 51(6): 1246-54.
• Meijerman L, Sholl S, De Conti F, Giacon M, Van der Lugt C, Drusini A, Vanezis P, Maat G. Exploratory study on classification and individualisation of earprints. Forensic Sci Int 2004; 140(1): 91-9.
• Rutty GN, Abbas A, Crossling D. Could ear-print identification be computerised? An illustrated proof of concept paper. Int J Legal Med 2005; 119(6): 335-43.
• Purkait R, Singh P. A test of individuality of human external ear pattern: its application in the field of personal identification. Forensic Sci Int 2008; 178(2-3): 112-8.
• Ventura F, Zacheo A, Ventura A, Pala A. Computerised anthropomorphometric analysis of images: case report. Forensic Sci Int 2004; 146(Supp l): S211-3.
• Hoogstrate AJ, Van Den Heuvel H, Huyben E. Ear identification based on surveillance camera images. Sci Justice 2001; 41(3): 167-72.
• Yan P, Bowyer KW. Biometric recognition using 3D ear shape. IEEE Trans Pattern Anal Mach Intell 2007; 29(8): 1297-308.
• Yoshino M, Matsuda H, Kubota S, Imaizumi K, Miyasaka S. Computer-assisted facial image identification system using a 3-D physiognomic range finder. Forensic Sci Int 2000; 109(3): 225-37.
• Pellnitz D. Über das Wachstum der menschlichen Ohrmuschel In: Archiv für Ohren-Nasen- und Kehlkopfheilkunde. Eur Arch Otorhinolaryngol 1958: 171(2): 334- 40.
• Hurley DJ, Nixon MS, Carter JN. Force field feature extraction for ear biometrics. Computer Vision and Image Understanding 2005; 98(3): 491-512.
• Alberink I, Ruifrok A. Performance of the FearID earprint identification system. Forensic Sci Int 2007; 166(2-3): 145-54.
• Kieckhoefer H, Ingleby M, Lucas G. Monitoring the physical formation of earprints: Optical and pressure mapping evidence. Measurement 2006; 39(10): 918-35. 23. Morgan J. State v. David Wayne Kunze. Available on: http://www.forensicevidence.com/site/ID/ID_Kunze.html, Accessed: May 15, 2010.
• Broeders AP. Of earprints, fingerprints, scent dogs, cot deaths and cognitive contamination--a brief look at the present state of play in the forensic arena. Forensic Sci Int. 2006; 159(2-3): 148-57.
• Graham EA, Bowyer VL, Martin VJ, Rutty GN. Investigation into the usefulness of DNA profiling of earprints. Sci Justice. 2007; 47(4): 155-9.
• McMurtrie J. The role of the social sciences in preventing wrongful convictions. 42 Am. Crim. L. Rev. 2005; 1271.