This paper proposes a novel approach to extract human hand gesture features in real-time from RGB-D images based on the earth mover’s distance and Lasso algorithms. Firstly, hand gestures with hand edge contour are segmented using a contour length information based de-noise method. A modified finger earth mover’s distance algorithm is then applied applied to locate the palm image and extract fingertip features. Lastly and more importantly, a Lasso algorithm is proposed to effectively and efficiently extract the fingertip feature from a hand contour curve. Experimental results are discussed to demonstrate the effectiveness of the proposed approach.