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EMOTION ESTIMATION FROM FACIAL IMAGES

Prediction of emotions from facial images is one of the popular and active researches, and it’s implemented via many methods. In this thesis, the proposed system to predict emotions from facial expressions images contains several stages, first stage of this system is the pre-processing stage which is applied by detecting the face in images, then resizing the images, and then Histogram Equalization (HE) technique is applied to normalize the effects of illumination. The second stage is extracting features from facial expressions images using Histogram of Oriented Gradient (HOG), and Local Binary Pattern (LBP) feature extraction algorithms, which generates the training dataset and the testing dataset that contains expressions of Anger, Contempt, Disgust, Embarrass, Fear, Happy, Neutral, Pride, Sad, and Surprised. Then Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classifiers are used for the classification stage in order to predict the emotion. In addition, Confusion Matrix (CM) technique is used to evaluate the performance of these classifiers. The proposed system is tested on JAFFE, KDEF, MUG, WSEFEP, TFEID and ADFES databases. However, the proposed system achieved prediction rate of 96.13% when HOG+SVM method is used. Keywords: Emotion estimation; Facial Expression Images; Expression Classification; Histogram of Oriented Gradient; Local Binary Pattern; K-Nearest Neighbors; Support Vector Machine.
جمعه محمد سالم نجاح, , (1-2017)
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أ. جمعه محمد سالم نجاح

أ. ‫جمعة نجاح هو أحد أعضاء هيئة التدريس بقسم الحاسوب بكلية التربية. يعمل السيد ‫جمعة بجامعة الزيتونة كـمحاضر مساعد منذ 2017-10-01 وله العديد من المنشورات العلمية في مجال تخصصه.