An Efficient Neuro-Fuzzy Classification System for Identifying Emotions

A person’s facial expressions reveal a great deal about their emotional state. The field of automated facial expression recognition holds great significance in the context of Human-Computer Interaction (HCI). The Wavelet Transform Features serve as the foundation for the suggested facial emotion identification technique. As texture characteristics, the image’s grey-level co-occurrence parameters and discrete wavelet transform image properties were employed. The neuro-fuzzy Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for classification. Validation of the suggested methodology’s performance yields encouraging results that demonstrate the recognition system’s efficacy.