Expressions are the voices that spell the mood of a person. To identify the emotions of the population and their underlying feelings like happy, sad, surprise, disgust need to be classified. The aim of this work is to recognize the emotions of people and classify them under the basic expressions categories. The research was carried on for color images for which segmentation based on a skin color helps to localize the face. The face is divided into three facial parts using horizontal and

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... projections. A Dataset is created by extracting the statistical features from each of the facial parts, and feature selection is implemented using a genetic algorithm based on the Root Mean Square Error (RMSE) that occurred while training the data with Naïve Bayes classifier. The algorithm has an accuracy of 92.31%.