Efficient regional multi feature similarity measure based emotion detection system in web portal using artificial neural network

Emotion detection from facial expression has been well studied. There are numerous techniques has been discussed for the accuracy of emotion detection, however the methods suffer with higher false classification ratio. Towards the development of emotion detection, a novel region based multi feature similarity approach has been presented in this article. Considering, shape and geometry measure alone would not acquire higher performance in the classification. It is necessary to consider and combine multiple features towards the problem. With this motivation, the proposed Regional Multi Feature Similarity (RMFS) based emotion detection algorithm enhances the input facial image and extracts shape feature, geometry feature and wrinkle features with colors are considered. Extracted features are trained with neural network. At the classification stage, MFS measure has been estimated towards the features of various emotion class in different layers of neural network. Finally, a single one has been classified as result using artificial neural network. The proposed method improves the performance of emotion detection with reduced false ratio.