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The human emotion recognition from face images based on textural analysis and linear classifier. Automatic facial expression recognition (FER) plays an important role in HCI systems for measuring people's emotions has dominated psychology by linking expressions to a group of basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). The recognition system involves face detection, features extraction and selection and finally classification. The face detection module will be used to obtain face images, which have normalized intensity, are uniform in size and shape and depict only the face region. The optimum features are selected using minimum redundancy maximum relevance algorithm based on mutual information (MI). The mutual information quotient (MIQ) method for feature selection is adopted to select the optimum features.