Face Recognition using Artificial Intelligent Techniques

  • Ibrahim L
  • Saleh I
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Abstract

Face recognition is considered one of the visual tasks which humans can do almost effortlessly while for computers it is a difficult and challenging task. This research deals with the problem of face recognition. A novel approach is presented for both face feature extraction and recognition, first, we introduce Principal Component Analysis (PCA) for face feature extraction, Generalized Regression Artificial Neural network for face recognition. The performance of the whole system was done after training with 120 color images (40 human faces with 3 poses) and testing using 40 color images. The images were taken from Collection of Facial Images: Faces95 by Computer Vision Science Research Projects. Experimental results for proposed human face recognition confirm that the proposed method lends itself to good extraction and classification accuracy relative to existing techniques. Keyword: Face Recognition, Artificial Intelligent Techniques ‫االصطناعيه‬ ‫الذكائيه‬ ‫التقنيات‬ ‫باستخدام‬ ‫الوجه‬ ‫تمييز‬ ‫ابراهيم‬ ‫محمد‬ ‫لهيب‬ ‫صالح‬ ‫احمد‬ ‫ابراهيم‬ ‫ياضيات‬ ‫الر‬ ‫و‬ ‫الحاسوب‬ ‫علوم‬ ‫كليه‬ ، ‫الموصل‬ ‫جامعه‬ :‫البحث‬ ‫استالم‬ ‫تاريخ‬ 03 / 06 / 2008 :‫البحث‬ ‫قبول‬ ‫تاريخ‬ 23 / 11 / 2008 ‫الملخص‬ ‫الوجه‬ ‫تمييز‬ ‫يعتبر‬ ‫أ‬ ‫ي‬ ‫البصر‬ ‫المهام‬ ‫حد‬ ‫ة‬ ‫ي‬ ‫ان‬ ‫يمكن‬ ‫التي‬ ‫نجزها‬ ‫ا‬ ‫أنها‬ ‫مع‬ ‫مشقة‬ ‫دون‬ ‫النسان‬ ‫المهام‬ ‫أصعب‬ ‫من‬ ‫تقديم‬ ‫تم‬ ‫وقد‬ .‫الحاسوب‬ ‫في‬ ‫أداء‬ ‫اص‬ ‫خو‬ ‫استخالص‬ ‫من‬ ‫لكل‬ ‫ة‬ ‫مبتكر‬ ‫يقة‬ ‫طر‬ ‫مشكله‬ ‫تناول‬ ‫ال‬ ‫أو‬ ‫تم‬ ‫إذ‬ ، ‫ه‬ ‫وتمييز‬ ‫الوجه‬ ‫تحليل‬ ‫باستخدام‬ ‫الوجه‬ ‫ة‬ ‫لصور‬ ‫اص‬ ‫الخو‬ ‫استخالص‬ ‫األساسية‬ ‫المكونات‬ (Principal Component Analysis (PCA). ‫الوجه‬ ‫تمييز‬ ‫وثانيا‬ ، ‫االصطنا‬ ‫العصبية‬ ‫الشبكة‬ ‫باستخدام‬ (‫عية‬ Generalized Regression Artificial Neural network (‫البيانات‬ ‫قاعدة‬ ‫باستخدام‬) faces95 ‫قسمت‬ ‫حيث‬ ‫المقترح‬ ‫النظام‬ ‫كفاءة‬ ‫تقييم‬ ‫في‬) (‫اقع‬ ‫بو‬ ‫يب‬ ‫التدر‬ ‫مجموعة‬ ‫األولى‬ ‫المجموعة‬ ،‫مجموعتين‬ ‫الى‬ ‫البيانات‬ ‫قاعدة‬ 120 ‫بمعدل‬ ‫ملونة‬ ‫ة‬ ‫صور‬) (40 ‫اما‬ ، ‫أوضاع‬ ‫بثالثة‬ ‫وجه‬ ‫لكل‬ ‫ة‬ ‫صور‬) (‫تضم‬ ‫التي‬ ‫االختبار‬ ‫مجموعة‬ ‫فهي‬ ‫الثانية‬ ‫المجموعة‬ 40) .‫الوجه‬ ‫لتمييز‬ ‫المقترح‬ ‫النظام‬ ‫على‬ ‫انجزت‬ ‫التي‬ ‫التجارب‬ ‫في‬ ‫جيدة‬ ‫نتائج‬ ‫على‬ ‫الحصول‬ ‫تم‬ ‫و‬ .‫ة‬ ‫صور‬ Laheeb M. Ibrahim & Ibrahim A. Saleh 212 ‫النتائج‬ ‫أثبتت‬ ‫و‬ ‫نة‬ ‫مقار‬ ‫عالية‬ ‫تصنيفها‬ ‫ودقه‬ ‫جيدة‬ ‫ه‬ ‫وتمييز‬ ‫الوجه‬ ‫الستخالص‬ ‫المستخدمة‬ ‫ائق‬ ‫الطر‬ ‫ان‬ .‫حاليا‬ ‫المتاحة‬ ‫بالتقنيات‬ :‫المفتاحيه‬ ‫الكلمات‬ ‫االصطناعيه‬ ‫العصبيه‬ ‫الشبكات‬ ،‫الوجه‬ ‫تمييز‬

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APA

Ibrahim, L., & Saleh, I. (2009). Face Recognition using Artificial Intelligent Techniques. AL-Rafidain Journal of Computer Sciences and Mathematics, 6(2), 211–227. https://doi.org/10.33899/csmj.2009.163809

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