Face Spoof Attack Recognition Using Discriminative Image Patches
المؤلفون المشاركون
Akhtar, Zahid
Foresti, Gian Luca
المصدر
Journal of Electrical and Computer Engineering
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-05-22
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Face recognition systems are now being used in many applications such as border crossings, banks, and mobile payments.
The wide scale deployment of facial recognition systems has attracted intensive attention to the reliability of face biometrics against spoof attacks, where a photo, a video, or a 3D mask of a genuine user’s face can be used to gain illegitimate access to facilities or services.
Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty in finding discriminative and computationally inexpensive features and methods for spoof attacks.
In addition, existing techniques use whole face image or complete video for liveness detection.
However, often certain face regions (video frames) are redundant or correspond to the clutter in the image (video), thus leading generally to low performances.
Therefore, we propose seven novel methods to find discriminative image patches, which we define as regions that are salient, instrumental, and class-specific.
Four well-known classifiers, namely, support vector machine (SVM), Naive-Bayes, Quadratic Discriminant Analysis (QDA), and Ensemble, are then used to distinguish between genuine and spoof faces using a voting based scheme.
Experimental analysis on two publicly available databases (Idiap REPLAY-ATTACK and CASIA-FASD) shows promising results compared to existing works.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Akhtar, Zahid& Foresti, Gian Luca. 2016. Face Spoof Attack Recognition Using Discriminative Image Patches. Journal of Electrical and Computer Engineering،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1108444
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Akhtar, Zahid& Foresti, Gian Luca. Face Spoof Attack Recognition Using Discriminative Image Patches. Journal of Electrical and Computer Engineering No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1108444
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Akhtar, Zahid& Foresti, Gian Luca. Face Spoof Attack Recognition Using Discriminative Image Patches. Journal of Electrical and Computer Engineering. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1108444
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1108444
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