Statistical gender analysis based on fingerprint ridge density

Ceyhan, Eyüp Burak; Sağıroğlu, Şeref; Akyil, M. E.

doi:10.1109/siu.2013.6531514

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…We observed from these steps and from our studies that women have higher ridge density than men in our country [24,25,28]. We developed a software for determining the finger we get the fingerprint from and cropped a 5x5mm area from the taken fingerprint.…”

Section: Country Average Ridge Countsmentioning

confidence: 99%

Parmak İzinden Cinsiyet Tahmini İçin Yeni Bir Zeki Sistem

Ceyhan

Sağıroğlu

2019

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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This paper proposes a new method for predicting genders from only fingerprints based on Artificial Neural Network (ANN) model. The modelling tasks are achieved by capturing fingerprints, analyzing an obtained fingerprint part (for example cropping 5x5mm part from a fingerprint image), determining ridges crossed by the diagonal of the obtained fingerprint part automatically, finding the ridge counts, ridge thicknesses, average fingerprint ridge counts of individuals, combining these features in a model, preparing and setting the structure of it and finally testing the model. The results of proposed model have shown that the best model achieves the task within 72% accuracy.

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Section: Country Average Ridge Countsmentioning

confidence: 99%

Parmak İzinden Cinsiyet Tahmini İçin Yeni Bir Zeki Sistem

Ceyhan

Sağıroğlu

2019

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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“…The result obtained from all these studies is that the ridge density average of women is 14.98 ridges/25mm 2 while the ridge density average of men is 13.20 ridges/25mm 2 . In our previous studies, the averages were found as 14.10 ridges/25mm 2 for Turkish women and 11.49 ridges/25mm 2 for Turkish men [11].…”

Section: Introductionmentioning

confidence: 75%

“…Based on this, we have done our research by considering that fingerprint ridge density of Turkish citizens is also different [11].…”

Section: A Aim Of the Studymentioning

confidence: 99%

Gender inference within Turkish population by using only fingerprint feature vectors

Ceyhan

Sağıroğlu

2014

2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)

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In the literature, there are some studies which investigate if there is a relationship between fingerprint and gender or not. In these studies, this relationship is examined based on some vectorial parts of fingerprints. The main problem in these studies is the lack of data, depending on ethnical background and country, and there is not an exact finding of true classification results. It is known that fingerprints show difference in males and females, and it is explained that women's line details are thin whereas men's line details are thick. However, the statistical studies, which have been made to prove the relationship between fingerprint and gender, have not investigated if the hypothesis is true for all ethnical backgrounds. In this study, we have examined if gender inference can be made only through fingerprint feature vectors, which belong to Turkish subjects, by using our database consisting of Naive Bayes, kNN, Decision Tree and Support Vector Machine learning algorithms. By using Naive Bayes algorithm, the success of the gender classification is found as 95.3%. This ratio has not been obtained before for "gender inference from fingerprint" in the literature. Therefore, this study can be useful for criminal cases.

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“…Fingerprints give some or more information about gender, origin, face sketch, age, etc. [18][19][20][21][22][23]26]. Ridge numbers and characteristics are generally worked on [9].…”

Section: Introductionmentioning

confidence: 99%

Parmak İzinden Cinsiyet Tahmininde 10 Parmak Arasındaki İlişkinin Analizi

Ceyhan¹,

Sağıroğlu²

2017

SAÜ Fen Bilimleri Enstitüsü Dergisi

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This study investigates the relationship among fingerprint and gender for all 10 fingerprints. 410 fingerprints taken from 19 females and 22 males aged between 18 and 25 years old were considered for this investigation. This is the first comprehensive study in literature that investigates 10 fingerprints for Turkish citizens. Ridge density, ridge thickness to valley thickness ratio and total ridge breadth values gained from our fingerprint database were used to determine gender. The results have shown that gender determination is successful for Turkish citizens with any of ten fingerprints. 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 of ridge density is determined as 1.34, which is the lowest value among the other studies in the literature.10 parmak öznitelikleri kullanılarak parmak izi ile cinsiyet arasındaki ilişkinin tespiti ÖZ Bu çalışma 10 parmak için parmak izi ve cinsiyet arasındaki ilişkiyi araştırmaktadır. Yaşları 18 ve 25 arasında olan 19 bayan ve 22 baydan alınan 410 parmak izi araştırma için değerlendirilmiştir. Bu çalışma Türk vatandaşlarının 10 parmak izini inceleyen literatürdeki ilk kapsamlı çalışmadır. Parmak izi veritabanımızdan elde edilen tepe yoğunluğu, tepe kalınlığının vadi kalınlığına oranı ve ortalama tepe genişliği değerleri cinsiyeti tespit etmek için kullanılmıştır. Sonuçlar, Türk vatandaşları için on parmaktan herhangi biri ile cinsiyet tespitinin başarılı olduğunu göstermektedir. Tepe kalınlığı-tepe genişliği-RTVTR için ortalama değerler baylar ve bayanlar için sırasıyla 13,09-36,56-0,46 ve 14,43-37,44-0,47'dir. Tepe yoğunluğunun cinsiyetler arasındaki farkı literatürdeki diğer çalışmalara göre en düşük değer olan 1,34 olarak tespit edilmiştir.

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Statistical gender analysis based on fingerprint ridge density

Cited by 5 publications

References 7 publications

Parmak İzinden Cinsiyet Tahmini İçin Yeni Bir Zeki Sistem

Parmak İzinden Cinsiyet Tahmini İçin Yeni Bir Zeki Sistem

Gender inference within Turkish population by using only fingerprint feature vectors

Parmak İzinden Cinsiyet Tahmininde 10 Parmak Arasındaki İlişkinin Analizi

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