Implementation of Image Processing and Classification Techniques on EEG Images for Emotion Recognition System

Abstract

The target paper aims at recognizing emotions using miscellaneous stimulus domains such as Electroencephalography (EEG) Images. The present study focuses on the recognition of emotions and extracting active regions, by using image processing and classification techniques. The study was performed using the data from 10 volunteers experiencing three emotional states relax, happy and sad. By applying thresholding and Sobel Edge detection technique, active regions were extracted. The Principle Component Analysis (PCA) and Linear Discriminate Analysis (LDA) classification techniques were enforced on the results respectively. The techniques resulted in effective outcomes, which can further be used for compelling Emotion Recognition System.
DOI: 10.17762/ijritcc2321-8169.1604118