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Facial Expression Recognition has become the preliminary research area due to its importance in human-computer interaction. Facial Expressions conveys the major part of information so it has vast applications in various fields. Many techniques have been developed in the literature but there is still a need to make the current expression recognition methods efficient. This paper represents proposed framework for face detection and recognizing six universal facial expressions such as happy, anger, disgust, fear, surprise, sad along with neutral face. Viola-Jones method and Face Landmark Detection method are used for face detection. Histogram of oriented gradients is used for feature extraction due to its superiority over other methods. To reduce the dimensionality of features Principal Component Analysis is used so that the maximum variation is preserved. Canberra distance classifier is used for classifying the expressions into different emotions. The proposed method is applied on Japanese Female Facial Expression Database and have evaluated that the proposed method outperforms many state-of-the-art techniques.