An Intelligent and Automatic Face Shape Prediction System From Fingerprints

Sağıroğlu, Şeref; Özkaya, Necla

doi:10.1080/10798587.2011.10643150

Cited by 9 publications

(14 citation statements)

References 5 publications

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“…The more related the individuals the most similar in appearance they, and vice visa. For example, parent and child have some genetic similarity as they share half of the genes, siblings have more similarity, and the maximum genetic similarity is observed in the identical twins, which bear the closest genetic relationship [26]. Several studies examined the correlation among faces and fingerprints of the identical twins [7,14,27,28].…”

Section: Classes Canon and Variationsmentioning

confidence: 99%

Evaluation of Facial Proportions and Their Association with Thumbprint Patterns among Hausa Ethnic Group

Adamu

Ojo

Danborno

et al. 2017

Journal of Anthropology

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Background. Evolutionary forces such as founder effect resulted in reproductive isolation and reduced genetic diversity may have led to ethnic variation in the facial appearance and other features like fingerprints pattern. Aim. To determine the pattern of facial proportion based on neoclassical facial canon. The associations between facial proportions and thumbprint patterns were also investigated. Subject and Methods. A total of 534 subjects of 18-25 years of age participated. Direct sensing and photographs methods were used to determine fingerprint and facial features, respectively. Fisher's Exact test was used to test for association between variables. Results. It was observed that in both males and females there was no (0%) occurrence of classical canon of facial proportion. There was also no association between sex and facial proportions. A significant association was found in between thumbprint patterns and vertical class III neoclassical facial proportion only when the frequency of both left and right thumbprint patterns was considered a single entity. There is no significant association between the thumbprint patterns of the right and left thumbs with vertical horizontal facial proportions in male and female participants. It was observed that right and left thumbs have more tendency of significance with facial proportion in males and females, respectively. Conclusion. Fingerprint pattern and its associated features may be controlled by a different mechanism such that the two may correlate differently with other features as the case may be with facial features.

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Section: Classes Canon and Variationsmentioning

confidence: 99%

Evaluation of Facial Proportions and Their Association with Thumbprint Patterns among Hausa Ethnic Group

Adamu

Ojo

Danborno

et al. 2017

Journal of Anthropology

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“…The concept of this new approach was introduced to the literature in different perspectives in the references [4][5][6][7][8][9][10][11][12][13][14][15]. This study is a further step of these previous studies to achieve, introduce and share this new concept with others around the world via web based platform.…”

Section: A Main Conceptmentioning

confidence: 98%

“…The authors have most recently introduced to literature for the first time that there have been close relationships among faces and fingerprints [3]. Generating the face borders, the face contours including face border and ears, the face models including eyebrows, eyes and mouth, the inner face parts including eyes, nose and mouth, the face parts including eyes, nose, mouth and ears and the face models including eyes, nose, mouth, ears and face border from only fingerprints without any need for face information have been the studies to introduce these relationships [4][5][6][7][8][9][10][11][12][13][14][15]. It is clear from these studies that a partially unknown biometric feature can be successfully achieved from a known biometric feature.…”

Section: Introductionmentioning

confidence: 99%

A Web Based Face Counter Prediction System from Only Fingerprints

Sağıroğlu

Yavanoğlu

2012

2012 11th International Conference on Machine Learning and Applications

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Up to now a large number of approaches and algorithms about biometric recognition techniques have been developed and proposed in the literature in details. Relationships about biometrics have recently been studied in the field by author research group. This paper presents a web based intelligent face mask prediction system based on artificial neural networks to predict faces from only fingerprint images. The aim of this study is to develop an online platform to be used by users, researchers or academics around the world. The results have been shown that the system can be used for live test through internet. The proposed web based system is successful to support and encourage researchers around the world to see and exercise this new concept in biometrics. The developed system predicts an appropriote face mask covering nose, eyes, ears and mouth from fingerprint images with the help of an intelligent model.

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“…Ridge numbers and characteristics are generally worked on [9]. In a recent study, Sagiroglu and Ozkaya have reported a study that predicts a person's face sketch from only fingerprints [16].…”

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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An Intelligent and Automatic Face Shape Prediction System From Fingerprints

Cited by 9 publications

References 5 publications

Evaluation of Facial Proportions and Their Association with Thumbprint Patterns among Hausa Ethnic Group

Evaluation of Facial Proportions and Their Association with Thumbprint Patterns among Hausa Ethnic Group

A Web Based Face Counter Prediction System from Only Fingerprints

Parmak İzinden Cinsiyet Tahmininde 10 Parmak Arasındaki İlişkinin Analizi

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