Performance of Face Recognition System Using Gradient Laplacian Operators and New Features Extraction Method Based on Linear Regression Slope
المؤلفون المشاركون
Bayat, Oguz
Ucan, Osman N.
Alazzawi, Abdulbasit
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-09-24
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Recent research proves that face recognition systems can achieve high-quality results even in non-ideal environments.
Edge detection techniques and feature extraction methods are popular mechanisms used in face recognition systems.
Edge detection can be used to construct the face map in the image efficiently, in which feature extraction techniques generate the most suitable features that can identify human faces.
In this study, we present a new and efficient face recognition system that uses various gradient-and Laplacian-based operators with a new feature extraction method.
Different edge detection operators are exploited to obtain the best image edges.
The new and robust method based on the slope of the linear regression, called SLP, uses the estimated face lines in its feature extraction step.
Artificial neural network (ANN) is used as a classifier.
To determine the best scheme that gives the best performance, we test combinations of various techniques such as (Sobel filter (SF), SLP/principal component analysis (PCA), ANN), (Prewitt filter(PF), SLP/PCA, ANN), (Roberts filter (RF), SLP/PCA, ANN), (zero cross filter (ZF), SLP/PCA, ANN), (Laplacian of Gaussian filter (LG), SLP/PCA, ANN), and (Canny filter(CF), SLP/PCA, ANN).
The BIO ID dataset is used in the training and testing phases for the proposed face recognition system combinations.
Experimental results indicate that the proposed schemes achieve satisfactory results with high-accuracy classification.
Notably, the combinations of (SF, SLP, ANN) and (ZF, SLP, ANN) gain the best results and outperform all the other algorithm combinations.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alazzawi, Abdulbasit& Ucan, Osman N.& Bayat, Oguz. 2018. Performance of Face Recognition System Using Gradient Laplacian Operators and New Features Extraction Method Based on Linear Regression Slope. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1205940
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Alazzawi, Abdulbasit…[et al.]. Performance of Face Recognition System Using Gradient Laplacian Operators and New Features Extraction Method Based on Linear Regression Slope. Mathematical Problems in Engineering No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1205940
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alazzawi, Abdulbasit& Ucan, Osman N.& Bayat, Oguz. Performance of Face Recognition System Using Gradient Laplacian Operators and New Features Extraction Method Based on Linear Regression Slope. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1205940
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1205940
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