FACIAL EXPRESSION EMOTION RECOGNITION USING LOCAL BINARY PATTERNS HISTOGRAMS

FACIAL EXPRESSION EMOTION RECOGNITION USING LOCAL BINARY PATTERNS HISTOGRAMS

Mrs.M.K.Nivodhini, Mr.B.Rajesh,

Department of computer science and engineering, K S R College of Engineering, Tiruchengode, Tamilnadu, India.

Department of computer science and engineering, K S R College of Engineering, Tiruchengode, Tamilnadu, India.

---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract: Local Binary Patterns (LBP) histograms are used as texture descriptors by the proposed facial expression emotion detection system to identify various face expressions in photos. Localized facial patterns are represented by histograms formed by the extraction of LBP features based on pixel intensity comparisons after pre-processing operations such as picture normalization and scaling. Using a labeled emotion dataset, these histograms are used as feature vectors to train a machine learning model. The model's performance is evaluated using evaluation measures, such as accuracy, precision, recall, and F1 score. The system, which was developed with OpenCV and scikit-learn, shows a reliable and useful method for recognizing facial expressions that can be used in practical settings.

Key Words: Facial Recognition, Deep Learning, Image Recognition