Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid
المؤلفون المشاركون
المصدر
Journal of Electrical and Computer Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-01-09
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
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.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, Yujia& Liu, Xin. 2018. Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184366
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, Yujia& Liu, Xin. Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1184366
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, Yujia& Liu, Xin. Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184366
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1184366
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر