A Secured Mobile Phone Based on Embedded Fingerprint Recognition Systems

2005 ◽  
pp. 549-553 ◽  
Author(s):  
Xinjian Chen ◽  
Jie Tian ◽  
Qi Su ◽  
Xin Yang ◽  
Fei Yue Wang
Keyword(s):  
Mobile Phone ◽  
Fingerprint Recognition ◽  
Recognition Systems

AUTHENTICATION OF FINGERPRINT BIOMETRICS ACQUIRED USING A CELLPHONE CAMERA: A REVIEW

2013 ◽  
Vol 11 (05) ◽  
pp. 1350033 ◽  
Author(s):  
MOHAMMED S. KHALIL ◽  
FAJRI KURNIAWAN ◽  
KASHIF SALEEM
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
High Performance ◽  
Personal Information ◽  
Current Trend ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Biometrics ◽  
Smart Mobile Phone ◽  
Smart Mobile

Over the past decade, there have been dramatic increases in the usage of mobile phones in the world. Currently available smart mobile phones are capable of storing enormous amounts of personal information/data. The smart mobile phone is also capable of connecting to other devices, with the help of different applications. Consequently, with these connections comes the requirement of security to protect personal information. Nowadays, in many applications, a biometric fingerprint recognition system has been embedded as a primary security measure. To enable a biometric fingerprint recognition system in smart mobile phones, without any additional costs, a built-in high performance camera can be utilized. The camera can capture the fingerprint image and generate biometric traits that qualify the biometric fingerprint authentication approach. However, the images acquired by a mobile phone are entirely different from the images obtained by dedicated fingerprint sensors. In this paper, we present the current trend in biometric fingerprint authentication techniques using mobile phones and explore some of the future possibilities in this field.

Application of Fingerprint-Matching Algorithm in Smart Gun Using Touch-Less Fingerprint Recognition System

2020 ◽  
pp. 122-128
Author(s):  
Saifullah Khalid
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Latent Fingerprint ◽  
Recognition Systems

Fingerprint recognition systems are widely used in the field of biometrics. Many existing fingerprint sensors acquire fingerprint images as the user's fingerprint is contacted on a solid flat sensor. Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems. For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact. While this system can solve the problems which arise through contact of the user's finger, other challenges emerge.

scholarly journals Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yujia Jiang ◽  
Xin Liu
Keyword(s):  
Local Binary Pattern ◽  
Fingerprint Recognition ◽  
Svm Classifier ◽  
Liveness Detection ◽  
Gaussian Pyramid ◽  
Detection Approach ◽  
Fingerprint Liveness Detection ◽  
Recognition Systems ◽  
Uniform Local Binary Pattern ◽  
High Recognition Accuracy

Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP) in spatial pyramid is applied to recognize fingerprint liveness in this paper. Firstly, preprocessing operation for each fingerprint is necessary. Then, to solve image rotation and scale invariance, three-layer spatial pyramids of fingerprints are introduced in this paper. Next, texture information for three layers spatial pyramids is described by using uniform local binary pattern to extract features of given fingerprints. The accuracy of our proposed method has been compared with several state-of-the-art methods in fingerprint liveness detection. Experiments based on standard databases, taken from Liveness Detection Competition 2013 composed of four different fingerprint sensors, have been carried out. Finally, classifier model based on extracted features is trained using SVM classifier. Experimental results present that our proposed method can achieve high recognition accuracy compared with other methods.

Security and matching of partial fingerprint recognition systems

2004 ◽  
Author(s):  
Tsai-Yang Jea ◽  
Viraj S. Chavan ◽  
Venu Govindaraju ◽  
John K. Schneider
Keyword(s):  
Fingerprint Recognition ◽  
Recognition Systems ◽  
Partial Fingerprint

From Biometrics Technology to Applications Regarding Face, Voice, Signature and Fingerprint Recognition Systems

2002 ◽  
pp. 289-337 ◽  
Author(s):  
Javier Ortega-Garcia ◽  
Joaquin Gonzalez-Rodriguez ◽  
Danilo Simon-Zorita ◽  
Santiago Cruz-Llanas
Keyword(s):  
Fingerprint Recognition ◽  
Recognition Systems
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