Parmak İzinden Cinsiyet Tahmininde 10 Parmak Arasındaki İlişkinin Analizi

Year 2017, Volume: 21 Issue: 4, 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

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