The population of deaf-mute in Taiwan is increasing every year. These deaf-mute persons usually use sign language to communicate with each other. However, most hearing persons cannot understand sign languages because they have not learned it. In order to let normal persons understand sign language, a sign language recognition system is necessary. In this paper, such a sign language recognition system is proposed. In the proposed system, a depth image is captured by Kinect sensor, palm area is segmented from depth image, palm binary image is thresholded by using Otsu thresholding method, and background noises are removed by morphological closing operators, and SURF features and descriptors are extracted to identify the sign language. Experimental results show that the proposed method is effective to detect and identify the numerals and letters in the English Alphabet used in the sign language.