Automatic recognition facial expressions and analysis of it has been an active topic for over decades. Different features extraction from salient features patches play a vital role in recognition of facial expression effectively. The critical step for recognition of facial expression recognition is to extract emotions features accurately. Facial expression recognition approaches consist of two main categories which are based on the type of features used in geometry-based features and appearance-based features. This paper shows the comparison in the performance of FER by automatically capturing facial movement features in static images based on distance features and expression recognition by using appearance features of selected facial patches.