Feature Extraction Model for Social Images

Extraction of appropriate features is a difficult task because it mainly depends on a specific application domain. In this paper, we presented a 5-layered feature extraction model for social images. This model extracts color, texture, geometric, and regional features from given image and also checks presence or absence of people in an image by face detection. Then, normalization of the feature vector is done with the help of priority element. Proposed model is able to deal with the heterogeneous nature of social images. It is useful to get good results in the field of social data analytics.