Parmak İzinden Cinsiyet Tahmininde 10 Parmak Arasındaki İlişkinin Analizi

Year 2017, , 740 - 749, 01.08.2017

Eyüp Burak Ceyhan , Şeref Sağıroğlu

https://doi.org/10.16984/saufenbilder.254153

Abstract

Bu
çalışma 10 parmak için parmak izleri ve cinsiyetler arasındaki ilişkileri
araştırmaktadır. Yaşları 18 ve 25 arasında olan 19 bayan ve 22 baydan alınan
410 parmak izi araştırma için değerlendirilmiştir. Bu çalışma Türk vatandaşları
için literatüre sunulan 10 parmak izi inceleyen ilk kapsamlı çalışmadır. Parmak
izi veritabanımızdan elde edilen tepe yoğunluğu, tepe kalınlığının vadi
kalınlığına oranı ve ortalama tepe genişliği değerleri cinsiyetleri
sınıflandırmak için kullanılmıştır. Sonuçlar, Türk vatandaşları için cinsiyet
sınıflandırmasının başarılı olduğunu göstermektedir. Tepe kalınlığı-tepe
genişliği-RTVTR için ortalama değerler baylar için 13,09-36,56-0,46 ve bayanlar
için 14,43-37,44-0,47’dir. Tepe yoğunluğunun cinsiyetler arasındaki farkı
literatürdeki diğer çalışmalara gore en düşük değer olan 1,34’dür.

Keywords

RTVTR, Parmak izi, tepe yoğunluğu, tepe genişliği, cinsiyet tahmini

Analysis of the Relationship Among 10 Fingers in Gender Predictionm from Fingerprints

Abstract

This study investigates the
relationships among fingerprints and genders for all 10 fingerprints. 410
fingerprints taking from 19 females and 22 males aged between 18 and 25 years
old were considered for this investigation. This is the first time
comprehensive study that investigates 10 fingerprints presented to the
literature for Turkish citizens. Ridge density, ridge thickness to valley
thickness ratio and total ridge breadth values gained from our fingerprint
database were used to classify genders. The results have shown that the gender
prediction is successful for Turkish citizens. The average values for ridge
density-ridge breadth-RTVTR are 13.09-36.56-0.46 for men and 14.43-37.44-0.47
for women, respectively. The gender difference for ridge density is 1.34, which
is the lowest value among the other studies in the literature.

Keywords

Fingerprint, ridge density, RTVTR, ridge breadth, gender prediction

References

• [1] E. Gutiérrez, V. Galera, J. M. Martínez, C. Alonso, Biological variability of the minutiae in the fingerprints of a sample of the Spanish population, Forensic Science International, 172(2–3) (2007) pp.98-105.
• [2] V.C. Nayak, P. Rastogi, T. Kanchan, K. Yoganarasimha, G.P. Kumar, R.G. Menezes, Sex differences from fingerprint ridge density in Chinese and Malaysian population, Forensic Science International, 197 (2010) pp.67–69.
• [3] E. Gutierrez-Redomero, N. Rivalderi, C. Alonso-Rodriguez, L.M. Martin, J.E. Dipierri, M.A. Fernandez-Peire, R. Morillo, Are there population differences in minutiae frequencies? A comparative study of two Argentinian population samples and one Spanish sample, Forensic Science International, 222 (2012) pp.266–276.
• [4] A. Badawi, M.R. Mahfouz, R. Tadross, R. Jantz, Fingerprint-based gender classification, International Conference on Image Processing, Computer Vision, & Pattern Recognition, Las Vegas, Nevada, USA, (2006) pp.41-46.
• [5] M.D. Nithin, B.M. Balaraj, B. Manjunatha, S.C. Mestri, Study of fingerprint classification and their gender distribution among South Indian population, Journal of Forensic and Legal Medicine, 16(8) (2009) pp.460-463.
• [6] D. Kimura, M.W. Carson, Dermatoglyphic asymmetry:relation to sex handedness and cognitive pattern, Personality and Individual Differences, 19(4) (1995) pp.471-478.
• [7] E. Gutierrez-Redomero, C. Alonso, V. Galera, Variability of fingerprint ridge density in a sample of Spanish Caucasians and its application to sex determination, Forensic Science International, 180 (2008) pp.17–22.
• [8] E. Gutiérrez-Redomero, M.C. Alonso, J.E. Dipierri, Sex differences in fingerprint ridge density in the Mataco-Mataguayo population, HOMO - Journal of Comparative Human Biology, 62 (2011) pp.487–499.
• [9] E. Gutiérrez-Redomero, A. Sánchez-Andrés, N. Rivaldería, C. Alonso-Rodríguez, J.E. Dipierri, L.M. Martín, A comparative study of topological and sex differences in fingerprint ridge density in Argentinian and Spanish population samples, Journal of Forensic and Legal Medicine, 20 (2013) pp.419-429.
• [10] K. Krishan, T. Kanchan, C. Ngangom, A study of sex differences in fingerprint ridge density in a North Indian young adult population, Journal of Forensic and Legal Medicine, 20 (2013) pp.217-222.
• [11] A.K. Agnihotri, V. Jowaheer, A. Allock, An analysis of fingerprint ridge density in the Indo-Mauritian population and its application to gender determination, Medicine, Science and the Law, 52(3) (2012) pp.143-147.
• [12] S. Nanakorn, P. Poosankam, A. Nanakorn, An Application of Automated Inkless Fingerprint Imaging Software in Fingerprint Collection and Pattern Analysis, IEEE Second International Conference on Innovative Computing, Information and Control (ICICIC '07), Kumamoto, Japan, (2007) pp.53.
• [13] M.D. Nithin, B. Manjunatha, D.S. Preethi, B.M. Balaraj, Gender differentiation by finger ridge count among South Indian population, Journal of Forensic and Legal Medicine, 18 (2011) pp.79-81.
• [14] V.C. Nayak, P. Rastogi, T. Kanchan, S.W. Lobo, K. Yoganarasimha, S. Nayak, N.G. Rao, G.P. Kumar, B.S.K. Shetty, R.G. Menezes, Sex differences from fingerprint ridge density in the Indian population, Journal of Forensic and Legal Medicine, 17 (2010) pp.84–86.
• [15] G.A. Eshak, J.F. Zaher, E.I. Hasan, A.A. Ewis, Sex identification from fingertip features in Egyptian population, Journal of Forensic and Legal Medicine, 20 (2013) pp.46-50.
• [16] S. Sagiroglu, N. Ozkaya, An Intelligent and Automatic Face Shape Prediction System From Fingerprints, Intelligent Automation & Soft Computing, 17(3) (2011) pp.309-317.
• [17] M.A. Acree, Is there a gender difference in fingerprint ridge density?, Forensic Science International, 102 (1999) pp.35–44.
• [18] E.B. Ceyhan, S. Sagiroglu, S. Tatoglu, E. Atagun, Age Estimation from Fingerprints: Examination of the Population in Turkey, IEEE 13th International Conference on Machine Learning and Applications (ICMLA), Detroit, USA, (2014) pp.478-481.
• [19] E.B. Ceyhan, S. Sagiroglu, E. Akyil, Gender Classification Based on ANN with Using Fingerprint Feature Vectors, Journal of the Faculty of Engineering and Architecture of Gazi University, 29(1) (2014) pp.201-207.
• [20] E.B. Ceyhan, S. Sagiroglu, Gender inference within Turkish population by using only fingerprint feature vectors, IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM), Orlando, USA, (2014) pp.146-150.
• [21] E.B. Ceyhan, S. Sagiroglu, M.E. Akyil, Statistical gender analysis based on fingerprint ridge density, IEEE 21st Signal Processing and Communications Applications Conference (SIU), Lefkosa, KKTC, (2013) pp.1-4.
• [22] S. Sagiroglu, U. Yavanoglu, E.B. Ceyhan, M.E. Akyil, System for estimating gender from fingerprints, US Patent App. 14/408,102.
• [23] R. Kaur, S.G. Mazumdar, Fingerprint Based Gender Identification Using Frequency Domain Analysis, International Journal of Advances in Engineering & Technology, 3(1) (2012) pp.295-299.
• [24] S. Cadd, M. Islam, P. Manson, S. Bleay, Fingerprint composition and aging: A literature review, Science & Justice, 55(4) (2015) pp.219-238.
• [25] E. Gutiérrez-Redomero, N. Rivaldería, C. Alonso-Rodríguez, Á. Sánchez-Andrés, Assessment of the methodology for estimating ridge density in fingerprints and its forensic application, Science & Justice, 54(3) (2014) pp.199-207.
• [26] Ceyhan, E.B., Intelligent system for identifying gender from fingerprint, MSc Thesis, Gazi University Institute of Science and Technology, Ankara (2012).