Robust detection and recognition system based on facial extraction and decision tree
المؤلفون المشاركون
Rashid, Ansam Hasan
Hamad, Muthanna H.
المصدر
Journal of Engineering and Sustainable Development
العدد
المجلد 25، العدد 4 (31 أغسطس/آب 2021)، ص ص. 40-50، 11ص.
الناشر
الجامعة المستنصرية كلية الهندسة
تاريخ النشر
2021-08-31
دولة النشر
العراق
عدد الصفحات
11
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
- التعلم الآلي
- الإدراك البصري
- التحليل متعدد المتغيرات
- الوجه
- التعرف على الأنماط
- معالجة الصور
- التحليل عبر المركبات الرئيسية
- خوارزميات الحاسوب
الملخص EN
Automatic face recognition system is suggested in this work on the basis of appearance based features focusing on the whole image as well as local based features focusing on critical face points like eyes, mouth, and nose for generating further details.
Face detection is the major phase in face recognition systems, certain method for face detection (Viola-Jones) has the ability to process images efficiently and achieve high rates of detection in real time systems.
Dimension reduction and feature extraction approaches are going to be utilized on the cropped image caused by detection.
One of the simple, yet effective ways for extracting image features is the Local Binary Pattern Histogram (LBPH), while the technique of Principal Component Analysis (PCA) was majorly utilized in pattern recognition.
Also, the technique of Linear Discriminant Analysis (LDA) utilized for overcoming PCA limitations was efficiently used in face recognition.
Furthermore, classification is going to be utilized following the feature extraction.
The utilized machine learning algorithms are PART and J48.
The suggested system is showing high accuracy for detection with Viola-Jones 98.75, whereas the features which are extracted by means of LDA with J48 provided the best results of (F-measure, Recall, and Automatic face recognition system is suggested in this work on the basis of appearance based features focusing on the whole image as well as local based features focusing on critical face points like eyes, mouth, and nose for generating further details.
Face detection is the major phase in face recognition systems, certain method for face detection (Viola-Jones) has the ability to process images efficiently and achieve high rates of detection in real time systems.
Dimension reduction and feature extraction approaches are going to be utilized on the cropped image caused by detection.
One of the simple, yet effective ways for extracting image features is the Local Binary Pattern Histogram (LBPH), while the technique of Principal Component Analysis (PCA) was majorly utilized in pattern recognition.
Also, the technique of Linear Discriminant Analysis (LDA) utilized for overcoming PCA limitations was efficiently used in face recognition.
Furthermore, classification is going to be utilized following the feature extraction.
The utilized machine learning algorithms are PART and J48.
The suggested system is showing high accuracy for detection with Viola-Jones 98.75, whereas the features which are extracted by means of LDA with J48 provided the best results of (F-measure, Recall, and Precision).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Rashid, Ansam Hasan& Hamad, Muthanna H.. 2021. Robust detection and recognition system based on facial extraction and decision tree. Journal of Engineering and Sustainable Development،Vol. 25, no. 4, pp.40-50.
https://search.emarefa.net/detail/BIM-1271293
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Rashid, Ansam Hasan& Hamad, Muthanna H.. Robust detection and recognition system based on facial extraction and decision tree. Journal of Engineering and Sustainable Development Vol. 25, no. 4 (2021), pp.40-50.
https://search.emarefa.net/detail/BIM-1271293
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Rashid, Ansam Hasan& Hamad, Muthanna H.. Robust detection and recognition system based on facial extraction and decision tree. Journal of Engineering and Sustainable Development. 2021. Vol. 25, no. 4, pp.40-50.
https://search.emarefa.net/detail/BIM-1271293
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
-
رقم السجل
BIM-1271293
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