Deaf and hard of hearing people communicate with others and within their own communities by using sign language. Computer recognition of sign language begins with the learning of sign gestures and continues through the production of text and speech. There are two types of sign gestures: static and dynamic. Both gesture recognition systems are crucial to the human community, even if static gesture recognition is easier than dynamic gesture recognition. We have conducted research on the steps required to convert static American sign language (ASL) to readable text and selected the best available methods to do so. Examined general steps are the data collection, pre-processing, transformation, feature extraction, and classification. There are also some recommendations for further study in this field.